Datasets:

debajyotidasgupta

/

dblp_2022_2023

like 0

Title: Blacktooth: Breaking through the Defense of Bluetooth in Silence Abstract: ABSTRACTBluetooth is a short-range wireless communication technology widely used by billions of personal computing, IoT, peripheral, and wearable devices. Bluetooth devices exchange commands and data, such as keyboard/mouse inputs, audio, and files, through a secure communication channel that is established through a pairing process. Due to the sensitivity of those commands and data, security mechanisms, such as encryption, authentication, and authorization, have been developed and adopted in the standards. Nevertheless, vulnerabilities continue to be discovered. In the literature, few successful attacks against the Bluetooth connection establishment stage have been reported. Many attacks simply assume that connections are already established or use a compromised agent, e.g, a malicious app or a careless user, to initialize the connection. We argue that such assumptions are strong and impractical. A stealthily established connection is a critical starting point for any practical attack against Bluetooth devices. In this paper, we demonstrate that the Bluetooth Specification contains a series of vulnerabilities that will enable an attacker to impersonate a Bluetooth device and successfully establish a connection with a victim device. The entire process does not require any involvement of the device owner/user or any malicious app on the victim device. The attacker could further escalate permissions by switching Bluetooth profiles to retrieve sensitive information from the victim device and inject arbitrary commands. We name our new attack as the Blacktooth Attack. To demonstrate the effectiveness and practicality of the Blacktooth attack, we evaluate it against 21 different Bluetooth devices with diverse manufacturers and operating systems, and all major Bluetooth versions. We show that the newly proposed attack is successful on all victim devices.

Title: Server-Aided Continuous Group Key Agreement Abstract: ABSTRACTContinuous Group Key Agreement (CGKA) -- or Group Ratcheting -- lies at the heart of a new generation of scalable End-to-End secure (E2E) cryptographic multi-party applications. One of the most important (and first deployed) CGKAs is ITK which underpins the IETF's upcoming Messaging Layer Security E2E secure group messaging standard. To scale beyond the group sizes possible with earlier E2E protocols, a central focus of CGKA protocol design is to minimize bandwidth requirements (i.e. communication complexity). In this work, we advance both the theory and design of CGKA culminating in an extremely bandwidth efficient CGKA. To that end, we first generalize the standard CGKA communication model by introducing server-aided CGKA (saCGKA) which generalizes CGKA and more accurately models how most E2E protocols are deployed in the wild. Next, we introduce the SAIK protocol; a modification of ITK, designed for real-world use, that leverages the new capabilities available to an saCGKA to greatly reduce its communication (and computational) complexity in practical concrete terms. Further, we introduce an intuitive, yet precise, security model for saCGKA. It improves upon existing security models for CGKA in several ways. It more directly captures the intuitive security goals of CGKA. Yet, formally it also relaxes certain requirements allowing us to take advantage of the saCGKA communication model. Finally, it is significantly simpler making it more tractable to work with and easier to build intuition for. As a result, the security proof of SAIK is also simpler and more modular. Finally, we provide empirical data comparing the (at times, quite dramatically improved) complexity profile of SAIK to state-of-the art CGKAs. For example, in a newly created group with 10K members, to change the group state (e.g. add/remove parties) ITK requires each group member download 1.38MB. However, with SAIK, members download no more than 2.7KB.

Title: Enforcing Fine-grained Constant-time Policies Abstract: ABSTRACTCryptographic constant-time (CT) is a popular programming discipline used by cryptographic libraries to protect themselves against timing attacks. The CT discipline aims to enforce that program execution does not leak secrets, where leakage is defined by a formal leakage model. In practice, different leakage models coexist, sometimes even within a single library, both to reflect different architectures and to accommodate different security-efficiency trade-offs. Constant-timeness is popular and can be checked automatically by many tools. However, most sound tools are focused on a baseline (BL) leakage model. In contrast, (sound) verification methods for other leakage models are less developed, in part because these models require modular arithmetic reasoning. In this paper, we develop a systematic, sound, approach for enforcing fine-grained constant-time policies beyond the BL model. Our approach combines two main ingredients: a verification infrastructure, which proves that source programs are constant-time, and a compiler infrastructure, which provably preserves constant-timeness for these fine-grained policies. By making these infrastructures parametric in the leakage model, we achieve the first approach that supports fine-grained constant-time policies. We implement the approach in the Jasmin framework for high-assurance cryptography, and we evaluate our approach with examples from the literature: OpenSSL and wolfSSL. We found a bug in OpenSSL and provided a formally verified fix.

Title: Post Quantum Noise Abstract: ABSTRACTWe introduce PQNoise, a post-quantum variant of the Noise framework. We demonstrate that it is possible to replace the Diffie-Hellman key-exchanges in Noise with KEMs in a secure way. A challenge is the inability to combine key pairs of KEMs, which can be resolved by certain forms of randomness-hardening for which we introduce a formal abstraction. We provide a generic recipe to turn classical Noise patterns into PQNoise patterns. We prove that the resulting PQNoise patterns achieve confidentiality and authenticity in the fACCE model. Moreover we show that for those classical Noise-patterns that have been conjectured or proven secure in the fACCE model our matching PQNoise patterns eventually achieve the same security. Our security proof is generic and applies to any valid PQNoise pattern. This is made possible by another abstraction, called a hash-object, which hides the exact workings of how keying material is processed in an abstract stateful object that outputs pseudorandom keys under different corruption patterns. We also show that the hash chains used in Noise are a secure hash-object. Finally, we demonstrate the practicality of PQNoise delivering benchmarks for several base patterns.

Title: Laconic Private Set-Intersection From Pairings Abstract: ABSTRACTPrivate set-intersection (PSI) is one of the most practically relevant special-purpose secure multiparty computation tasks, as it is motivated by many real-world applications. In this paper we present a new private set-intersection protocol which is laconic, meaning that the protocol only has two rounds and that the first message is independent of the set sizes. Laconic PSI can be useful in applications, where servers with large sets would like to learn the intersection of their set with smaller sets owned by resource-constrained clients and where multiple rounds of interactions are not possible. Previously, practically relevant laconic PSI protocols were only known from factoring-type assumptions. The contributions of this work are twofold: 1) We present the first laconic PSI protocol based on assumptions over pairing-friendly elliptic curves; and 2) For the first time we provide empirical evaluation of any laconic PSI protocol by carefully implementing and optimizing both our and previous protocols. Our experimental results shows that our protocol outperforms prior laconic PSI protocols.

Title: Efficient Secure Three-Party Sorting with Applications to Data Analysis and Heavy Hitters Abstract: ABSTRACTWe present a three-party sorting protocol secure against passive and active adversaries in the honest majority setting. The protocol can be easily combined with other secure protocols which work on shared data, and thus enable different data analysis tasks, such as private set intersection of shared data, deduplication, and the identification of heavy hitters. The new protocol computes a stable sort. It is based on radix sort and is asymptotically better than previous secure sorting protocols. It improves on previous radix sort protocols by not having to shuffle the entire length of the items after each comparison step. We implemented our sorting protocol with different optimizations and achieved concretely fast performance. For example, sorting one million items with 32-bit keys and 32-bit values takes less than 2 seconds with semi-honest security and about 3.5 seconds with malicious security. Finding the heavy hitters among hundreds of thousands of 256-bit values takes only a few seconds, compared to close to an hour in previous work.

Title: Chaghri - A FHE-friendly Block Cipher Abstract: ABSTRACTThe Recent progress in practical applications of secure computation protocols has also attracted attention to the symmetric-key primitives underlying them. Whereas traditional ciphers have evolved to be efficient with respect to certain performance metrics, advanced cryptographic protocols call for a different focus. The so called arithmetic complexity is viewed through the number and layout of non-linear operations in the circuit implemented by the protocol. Symmetric-key algorithms that are optimized with respect to this metric are said to be algebraic ciphers. Previous work targeting ZK and MPC protocols delivered great improvement in the performance of these applications both in lab and in practical use. Interestingly, despite its apparent benefits to privacy-aware cloud computing, algebraic ciphers targeting FHE did not attract similar attention. In this paper we present Chaghri, an FHE-friendly block cipher enabling efficient transciphering in BGV-like schemes. A complete Chaghri circuit can be implemented using only 16 multiplications, 48 Frobenius automorphisms and 32 rotations, all arranged in a depth-32 circuit. Our HElib implementation achieves a throughput of 0.28 seconds-per-bit which is 63% faster thanAES in the same setting.

Title: Secure Parallel Computation on Privately Partitioned Data and Applications Abstract: ABSTRACTParallel computation is an important aspect of multi-party computation, not only in terms of improving efficiency, but also in terms of providing privacy for computation involving conditional branching based on private data. While applying multi-party computation in parallel over several sets of input data is straightforward if the partitioning of the input data into sets is publicly known, the problem becomes much more challenging when this partitioning is private. This setting is relevant to broad class of secure computations, in particular to secure graph and database analysis in which the underlying data (graph or database) is private. In this paper, we consider a general class of functions which can be expressed via the iterative evaluation of a binary associative operation, and propose efficient protocols for evaluating such functions in parallel over privately partitioned input data. Our protocols are optimal in terms of the required number of evaluations of the underlying binary operation (i.e.\ N-1 evaluations for total input size N), while simultaneously achieving a round complexity which is only logarithmic in the total size of the input data (i.e.\ O(łog N)). Applying our protocols to specific functions result in concrete improvements compared to dedicated protocols from previous works. For example, we improve upon the previously best known protocols for simple functionalities such as (grouped) summation and (grouped) max, as well as the secure graph analysis protocols by Nayak et al. ~(S&P'15), which all requires O(N łog N) evaluations of their respective underlying operations to achieve a O(łog N) round complexity. While our protocols achieve the same asymptotic performance as the shortest path algorithms by Anagreh et al. ~(Cryptography'21), we achieve better concrete performance. Lastly, considering shortest path computations on a weighted graph via the Bellman-Ford algorithm, we reduce the communication complexity by 2.4\sim 5.4 compared to the recent results by Araki et al. \ (CCS'21) on large-scale graphs of thousand nodes and edges. Besides this, we achieve efficient protocols for functions not considered previously, such as ArgMax, first/last projections, and list concatenation.

Title: Thora: Atomic and Privacy-Preserving Multi-Channel Updates Abstract: ABSTRACTMost blockchain-based cryptocurrencies suffer from a heavily limited transaction throughput, which is a barrier to their growing adoption. Payment channel networks (PCNs) are one of the promising solutions to this problem. PCNs reduce the on-chain load of transactions and increase the throughput by processing many payments off-chain. In fact, any two users connected via a path of payment channels (i.e., joint addresses between the two channel end-points) can perform payments, and the underlying blockchain is used only when there is a dispute between users. Unfortunately, payments in PCNs can only be conducted securely along a path, which prevents the design of many interesting applications. Moreover, the most widely used implementation, the Lightning Network in Bitcoin, suffers from a collateral lock time linear in the path length, it is affected by security issues, and it relies on specific scripting features called Hash Timelock Contracts that hinders the applicability of the underlying protocol in other blockchains. In this work, we present Thora, the first Bitcoin-compatible off-chain protocol that enables the atomic update of arbitrary channels (i.e., not necessarily forming a path). This enables the design of a number of new off-chain applications, such as payments across different PCNs sharing the same blockchain, secure and trustless crowdfunding, and channel rebalancing. Our construction requires no specific scripting functionalities other than digital signatures and timelocks, thereby being applicable to a wider range of blockchains. We formally define security and privacy in the Universal Composability framework and show that our cryptographic protocol is a realization thereof. In our performance evaluation, we show that our construction requires only constant collateral, independently from the number of channels, and has only a moderate off-chain communication as well as computation overhead.

Title: Sleepy Channels: Bi-directional Payment Channels without Watchtowers Abstract: ABSTRACTPayment channels (PC) are a promising solution to the scalability issue of cryptocurrencies, allowing users to perform the bulk of the transactions off-chain without needing to post everything on the blockchain. Many PC proposals however, suffer from a severe limitation: Both parties need to constantly monitor the blockchain to ensure that the other party did not post an outdated transaction. If this event happens, the honest party needs to react promptly and engage in a punishment procedure. This means that prolonged absence periods (e.g., a power outage) may be exploited by malicious users. As a mitigation, the community has introduced watchtowers, a third-party monitoring the blockchain on behalf of off-line users. Unfortunately, watchtowers are either trusted, which is critical from a security perspective, or they have to lock a certain amount of coins, called collateral, for each monitored PC in order to be held accountable, which is financially infeasible for a large network. We present Sleepy Channels, the first bi-directional PC protocol without watchtowers (or any other third party) that supports an unbounded number of payments and does not require parties to be persistently online. The key idea is to confine the period in which PC updates can be validated on-chain to a short, pre-determined time window, which is when the PC parties have to be online. This behavior is incentivized by letting the parties lock a collateral in the PC, which can be adjusted depending on their mutual trust and which they get back much sooner if they are online during this time window. Our protocol is compatible with any blockchain that is capable of verifying digital signatures (e.g., Bitcoin), as shown by our proof of concept. Moreover, our experimental results show that Sleepy Channels impose a communication and computation overhead similar to state-of-the-art PC protocols while removing watchtower's collateral and fees for the monitoring service.

Title: On the Adaptive Security of the Threshold BLS Signature Scheme Abstract: ABSTRACTThreshold signatures are a crucial tool for many distributed protocols. As shown by Cachin, Kursawe, and Shoup (PODC '00), schemes with unique signatures are of particular importance, as they allow to implement distributed coin flipping very efficiently and without any timing assumptions. This makes them an ideal building block for (inherently randomized) asynchronous consensus protocols. The threshold-BLS signature of Boldyreva (PKC '03) is both unique and very compact, but unfortunately lacks a security proof against adaptive adversaries. Thus, current consensus protocols either rely on less efficient alternatives or are not adaptively secure. In this work, we revisit the security of the threshold BLS signature by showing the following results, assuming t adaptive corruptions: - We give a modular security proof that follows a two-step approach: 1) We introduce a new security notion for distributed key generation protocols (DKG). We show that it is satisfied by several protocols that previously only had a static security proof. 2) Assuming any DKG protocol with this property, we then prove unforgeability of the threshold BLS scheme. Our reductions are tight and can be used to substantiate real-world parameter choices. - To justify our use of strong assumptions such as the algebraic group model (AGM) and the hardness of one-more-discrete logarithm (OMDL), we prove an impossibility result: Even in the AGM, a strong interactive assumption is required in order to prove the scheme secure.

Title: Secret-Shared Joins with Multiplicity from Aggregation Trees Abstract: ABSTRACTWe present novel protocols to compute SQL-like join operations on secret shared database tables with non-unique join keys. Previous approaches to the problem had the restriction that the join keys of both the input tables must be unique or had quadratic overhead. Our work lifts this restriction, allowing one or both of the secret shared input tables to have an unknown and unbounded number of repeating join keys while achieving efficient O(n log n) asymptotic communication/computation and O(log n) rounds of interaction, independent of the multiplicity of the keys. We present two join protocols, Join-OM and Join-MM. The first, Join-OM is optimized for the case where one table has a unique primary key while the second, Join-MM is for the more general setting where both tables contain duplicate keys. Both protocols require O(n log n) time and O(log n) rounds to join two tables of size n. Our framework for computing joins requires an efficient sorting protocol and generic secure computation for circuits. We concretely instantiate our protocols in the honest majority three-party setting. Our join protocols are built around an efficient method to compute structured aggregations over a secret shared input vector V in D^n. If the parties have another secret-shared vector of control bits B in 0, 1 ^n to partition V into sub-vectors (that semantically relates to the join operations). A structured aggregation computes a secret shared vector V' in D^n where every sub-vector (V_b, ..., V_e) (defined by the control bits) is aggregated as V_i'= V_b op ... op V_i for i in b, ..., e according to some user-defined operator op. Critically, the b, e indices that partition the vector are secret. It's trivial to compute aggregations by sequentially processing the input vector and control bits. This would require O(n) rounds and would be very slow due to network latency. We introduce Aggregation Trees as a general technique to compute aggregations in O(log n) rounds. For our purpose of computing joins, we instantiate op in copy previous value, add, but we believe that this technique is quite powerful and can find applications in other useful settings.

Title: META-BTS: Bootstrapping Precision Beyond the Limit Abstract: ABSTRACTBootstrapping, which enables the full homomorphic encryption scheme that can perform an infinite number of operations by restoring the modulus of the ciphertext with a small modulus, is an essential step in homomorphic encryption. However, bootstrapping is the most time and memory consuming of all homomorphic operations. As we increase the precision of bootstrapping, a large amount of computational resources is required. Specifically, for any of the previous bootstrap designs, the precision of bootstrapping is limited by rescaling precision. In this paper, we propose a new bootstrapping algorithm of the Cheon-Kim-Kim-Song (CKKS) \citeCKKS17 scheme to use a known bootstrapping algorithm repeatedly, so called Meta-BTS. By repeating the original bootstrapping operation twice, one can obtain another bootstrapping with its precision essentially doubled; it can be generalized to be k-fold bootstrapping operations for some k>1 while the ciphertext size is large enough. Our algorithm overcomes the precision limitation given by the rescale operation.

Title: i-TiRE: Incremental Timed-Release Encryption or How to use Timed-Release Encryption on Blockchains? Abstract: ABSTRACTTimed-release encryption can encrypt a message to a future time such that it can only be decrypted after that time. Potential applications include sealed bid auctions, scheduled confidential transactions, and digital time capsules. To enable such applications as decentralized smart contracts, we explore how to use timed-release encryption on blockchains. Practical constructions in the literature rely on a trusted server (or servers in a threshold setting), which periodically publishes an epoch-specific decryption key based on a long-term secret. Their main idea is to model time periods or epochs as identities in an identity-based encryption scheme. However, these schemes suffer from a fatal flaw: an epoch's key does not let us decrypt ciphertexts locked to prior epochs. Paterson and Quaglia [SCN'10] address this concern by having encryption specify a range of epochs when decryption is allowed. However, we are left with an efficiency concern: in each epoch, the server(s) must publish (via a smart contract transaction) a decryption key of size logarithmic in the lifetime (total number of epochs). For instance, on Ethereum, for a modest lifetime spanning 2 years of 1-minute long epochs, a server must spend over \6 in gas fees, every minute; this cost multiplies with the number of servers in a threshold setting. We propose a novel timed-release encryption scheme, where a decryption key, while logarithmic in size, allows incremental updates, wherein a short update key (single group element) is sufficient to compute the successive decryption key; our decryption key lets the client decrypt ciphertexts locked to any prior epoch. This leads to significant reduction is gas fees, for instance, only \0.30 in the above setting. Moreover, ciphertexts are also compact (logarithmic in the total lifetime), and encryption and decryption are on the order of few milliseconds. Furthermore, we decentralize the trust among a number of servers, so as to tolerate up to a threshold number of (malicious) corruptions. Our construction is based on bilinear pairing, and adapts ideas from Canetti et al.'s binary tree encryption [Eurocypt 2003] and Naor et al.'s distributed pseudorandom functions [Eurocrypt 1999].

Title: Tidy: Symbolic Verification of Timed Cryptographic Protocols Abstract: ABSTRACTTimed cryptography refers to cryptographic primitives designed to meet their security goals only for a short (polynomial) amount of time. Popular examples include timed commitments and verifiable delay functions. Such primitives are commonly used to guarantee fairness in multiparty protocols ("either none or all parties obtain the output of the protocol'') without relying on any trusted party. Despite their recent surge in popularity, timed cryptographic protocols remain out of scope of current symbolic verification tools, which idealise cryptographic primitives as algebraic operations, and thus do not consider fine-grained notions of time. In this paper, we develop, implement, and evaluate a symbolic approach for reasoning about protocols built from timed cryptographic primitives. First, we introduce a timed extension of the applied pi-calculus, a common formalism to specify cryptographic protocols. Then, we develop a logic for timed hyperproperties capturing many properties of interest, such as timeliness or time-limited indistinguishability. We exemplify the usefulness of our approach by modelling a variety of cryptographic protocols, such as distributed randomness generation, sealed-bid auctions, and contract signing. We also study the decidability of timed security properties. On the theoretical side, we reduce the decision of hyperproperties expressed in our logic to a form of constraint solving generalising standard notions in protocol analysis, and showcase the higher complexity of the problem compared to similar well-established logics through complexity lower bounds. On the automation side, we mechanise proofs of timed safety properties by relying on the Tamarin tool as a backend, a popular symbolic protocol analyser, and validate several examples with our approach.

Title: Feta: Efficient Threshold Designated-Verifier Zero-Knowledge Proofs Abstract: ABSTRACTZero-Knowledge protocols have increasingly become both popular and practical in recent years due to their applicability in many areas such as blockchain systems. Unfortunately, public verifiability and small proof sizes of zero-knowledge protocols currently come at the price of strong assumptions, large prover time, or both, when considering statements with millions of gates. In this regime, the most prover-efficient protocols are in the designated verifier setting, where proofs are only valid to a single party that must keep a secret state. In this work, we bridge this gap between designated-verifier proofs and public verifiability by distributing the verifier efficiently. Here, a set of verifiers can then verify a proof and, if a given threshold t of the n verifiers is honest and trusted, can act as guarantors for the validity of a statement. We achieve this while keeping the concrete efficiency of current designated-verifier proofs, and present constructions that have small concrete computation and communication cost. We present practical protocols in the setting of threshold verifiers with t

Title: Distributed, Private, Sparse Histograms in the Two-Server Model Abstract: ABSTRACTWe consider the computation of sparse, (ε, ϑ)-differentially private~(DP) histograms in the two-server model of secure multi-party computation~(MPC), which has recently gained traction in the context of privacy-preserving measurements of aggregate user data. We introduce protocols that enable two semi-honest non-colluding servers to compute histograms over the data held by multiple users, while only learning a private view of the data. Our solution achieves the same asymptotic l∞-error of O(log(1/ϑoverε) as in the central model of DP, but without relying on a trusted curator. The server communication and computation costs of our protocol are independent of the number of histogram buckets, and are linear in the number of users, while the client cost is independent of the number of users, ε, and ϑ. Its linear dependence on the number of users lets our protocol scale well, which we confirm using microbenchmarks: for a billion users, ε = 0.5, and ϑ = 10-11, the per-user cost of our protocol is only 1.08 ms of server computation and 339 bytes of communication. In contrast, a baseline protocol using garbled circuits only allows up to 106 users, where it requires 600 KB communication per user.

Title: Threshold Cryptography as a Service (in the Multiserver and YOSO Models) Abstract: ABSTRACTWe consider large deployments of threshold cryptographic services that can run in traditional multi-server settings and, at a much larger scale, in blockchain environments. We present a set of techniques that improve performance and meet the requirements of settings with large number of servers and high rate of threshold operations. More fundamentally, our techniques enable threshold cryptographic applications to run in more challenging decentralized permissionless systems, such as contemporary blockchains. In particular, we design and implement a novel threshold solution for the recently introduced YOSO (You Only Speak Once) model. The model builds on ever changing, unpredictable committees that perform ephemeral roles in a way that evades targeting by attackers and enables virtually unlimited scalability in very large networks. Our solution allows for the maintenance of system-wide keys that can be generated, used and proactivized as needed. The specific techniques build on optimized protocols for multi-secret multi-dealer verifiable secret sharing and their adaptation to the YOSO model. We demonstrate the practicality of our solutions by reporting on an end-to-end implementation of a proactive re-sharing protocol in the YOSO model, showing benchmarks for committees of sizes up to 500 nodes. For traditional multi-server settings, we obtain significant speedups in settings where dealers process many secrets simultaneously (say, to generate or proactivize many keys at the same time), e.g., we show 5X improvements relative to classical Pedersen VSS for 15 servers and 50 secrets, and 48X for 500 servers and 1000 secrets.

Title: JIT-Picking: Differential Fuzzing of JavaScript Engines Abstract: ABSTRACTModern JavaScript engines that power websites and even full applications on the Web are driven by the need for an increasingly fast and snappy user experience. These engines use several complex and potentially error-prone mechanisms to optimize their performance. Unsurprisingly, the inevitable complexity results in a huge attack surface and varioustypes of software vulnerabilities. On the defender's side, fuzz testing has proven to be an invaluable tool for uncovering different kinds of memory safety violations. Although it is difficult to test interpreters and JIT compilers in an automated way, recent proposals for input generation based on grammars or target-specific intermediate representations helped uncovering many software faults. However, subtle logic bugs and miscomputations that arise from optimization passes in JIT engines continue to elude state-of-the-art testing methods. While such flaws might seem unremarkable at first glance, they are often still exploitable in practice. In this paper, we propose a novel technique for effectively uncovering this class of subtle bugs during fuzzing. The key idea is to take advantage of the tight coupling between a JavaScript engine's interpreter and its corresponding JIT compiler as a domain-specific and generic bug oracle, which in turn yields a highly sensitive fault detection mechanism. We have designed and implemented a prototype of the proposed approach in a tool called JIT-Picker. In an empirical evaluation, we show that our method enables us to detect subtle software faults that prior work missed. In total, we uncovered 32 bugs that were not publicly known and received a $10.000 bug bounty from Mozilla as a reward for our contributions to JIT engine security.

Title: A Symbolic Analysis of Privacy for TLS 1.3 with Encrypted Client Hello Abstract: ABSTRACTTLS 1.3, the newest version of the Transport Layer Security (TLS) protocol, provides strong authentication and confidentiality guarantees that have been comprehensively analyzed in a variety of formal models. However, despite its controversial use of handshake meta-data encryption, the privacy guarantees of TLS 1.3 remain weak and poorly understood. For example, the protocol reveals the identity of the target server to network attackers, allowing the passive surveillance and active censorship of TLS connections. To close this gap, the IETF TLS working group is standardizing a new privacy extension called Encrypted Client Hello (ECH, previously called ESNI), but the absence of a formal privacy model makes it hard to verify that this extension works. Indeed, several early drafts of ECH were found to be vulnerable to active network attacks. In this paper, we present the first mechanized formal analysis of privacy properties for the TLS 1.3 handshake. We study all standard modes of TLS 1.3, with and without ECH, using the symbolic protocol analyzer ProVerif. We discuss attacks on ECH, some found during the course of this study, and show how they are accounted for in the latest version. Our analysis has helped guide the standardization process for ECH and we provide concrete privacy recommendations for TLS implementors. We also contribute the most comprehensive model of TLS 1.3 to date, which can be used by designers experimenting with new extensions to the protocol. Ours is one of the largest privacy proofs attempted using an automated verification tool and may be of general interest to protocol analysts.

Title: Power Contracts: Provably Complete Power Leakage Models for Processors Abstract: ABSTRACTThe protection of cryptographic software implementations against power-analysis attacks is critical for applications in embedded systems. A commonly used algorithmic countermeasure against these attacks is masking, a secret-sharing scheme that splits a sensitive computation into computations on multiple random shares. In practice, the security of masking schemes relies on several assumptions that are often violated by microarchitectural side-effects of CPUs. Many past works address this problem by studying these leakage effects and building corresponding leakage models that can then be integrated into a software verification workflow. However, these models have only been derived empirically, putting in question the otherwise rigorous security statements made with verification. We solve this problem in two steps. First, we introduce a contract layer between the (CPU) hardware and the software that allows the specification of microarchitectural side-effects on masked software in an intuitive language. Second, we present a method for proving the correspondence between contracts and CPU netlists to ensure the completeness of the specified leakage models. Then, any further security proofs only need to happen between software and contract, which brings benefits such as reduced verification runtime, improved user experience, and the possibility of working with vendor-supplied contracts of CPUs whose design is not available on netlist-level due to IP restrictions. We apply our approach to the popular RISC-V IBEX core, provide a corresponding formally verified contract, and describe how this contract could be used to verify masked software implementations.

Title: Themis: An On-Site Voting System with Systematic Cast-as-intended Verification and Partial Accountability Abstract: ABSTRACTWe propose an on-site voting system Themis, that aims at improving security when local authorities are not fully trusted. Voters vote thanks to voting sheets as well as smart cards that produce encrypted ballots. Electronic ballots are systematically audited, without compromising privacy. Moreover, the system includes a precise dispute resolution procedure identifying misbehaving parties in most cases. We conduct a full formal analysis of Themis using ProVerif, with a novel approach in order to cover the modular arithmetic needed in our protocol. In order to evaluate the usability of our system, we organized a voting experiment on a (small) group of voters.

Title: Victory by KO: Attacking OpenPGP Using Key Overwriting Abstract: ABSTRACTWe present a set of attacks on the OpenPGP specification and implementations of it which result in full recovery of users' private keys. The attacks exploit the lack of cryptographic binding between the different fields inside an encrypted private key packet, which include the key algorithm identifier, the cleartext public parameters, and the encrypted private parameters. This allows an attacker who can overwrite certain fields in OpenPGP key packets to perform cross-algorithm attacks, causing a user's software to, for example, misinterpret an ECC private key as being a DSA key. It also allows an attacker to replace the legitimate public parameters with adversarially chosen ones, e.g. allowing them to select the DSA group. We refer to this class of attacks as Key Overwriting (KO) attacks. We provide a detailed analysis of the vulnerability of different OpenPGP libraries to KO attacks, showing in particular that in some cases additional key validation steps performed by libraries that should prevent the attacks in fact allow variant attacks. We also assess the applicability of KO attacks in the context of specific OpenPGP-based applications that reflect different threat models. Finally, we explain how KO attacks can be completely prevented (and the need for key validation obsoleted) at the OpenPGP specification level by expanding the existing proposal of using AEAD schemes for key packet protection to have all the security-relevant public fields included as Associated Data.

Title: Do Opt-Outs Really Opt Me Out? Abstract: ABSTRACTOnline trackers, such as advertising and analytics services, have provided users with choices to opt out of their tracking and data collection to mitigate the users' concerns about increased privacy risks. While opt-out choices of online services for the cookies placed on their own websites have been examined before, the choices provided by trackers for their third-party tracking services on publisher websites have been largely overlooked. There is no guarantee that a tracker's opt-out options would faithfully follow the statements in its privacy policy. To address this concern, we develop an automated framework, called OptOutCheck, that analyzes (in)consistencies between trackers' data practices and the opt-out choice statements in their privacy policies. We create sentence-level classifiers, which achieve ≥ 84.6% precision on previously-unseen statements, to extract the opt-out policies that state neither tracking nor data collection for opted-out users from trackers' privacy-policy documents. tOptOutCheck analyzes both tracker and publisher websites to detect opt-out buttons, perform the opt-out, and extract the data flows to the tracker servers after the user opts out. Finally, we formalize the opt-out policies and data flows to derive logical conditions to detect the inconsistencies. In a large-scale study of 2.9k popular trackers, OptOutCheck detected opt-out choices on 165 trackers and found 11 trackers who exhibited data practices inconsistent with their stated opt-out policies. Since inconsistencies are violations of the trackers' privacy policies and demonstrate data collection without user consent, they are likely to lose users' trust in the online trackers and trigger the necessity of an automatic auditing process.

Title: Vizard: A Metadata-hiding Data Analytic System with End-to-End Policy Controls Abstract: ABSTRACTOwner-centric control is a widely adopted method for easing owners' concerns over data abuses and motivating them to share their data out to gain collective knowledge. However, while many control enforcement techniques have been proposed, privacy threats due to the metadata leakage therein are largely neglected in existing works. Unfortunately, a sophisticated attacker can infer very sensitive information based on either owners' data control policies or their analytic task participation histories (e.g., participating in a mental illness or cancer study can reveal their health conditions). To address this problem, we introduce Vizard, a metadata-hiding analytic system that enables privacy-hardened and enforceable control for owners. Vizard is built with a tailored suite of lightweight cryptographic tools and designs that help us efficiently handle analytic queries over encrypted data streams coming in real-time (like heart rates). We propose extension designs to further enable advanced owner-centric controls (with AND, OR, NOT operators) and provide owners with release control to additionally regulate how the result should be protected before deliveries. We develop a prototype of Vizard that is interfaced with Apache Kafka, and the evaluation results demonstrate the practicality of Vizard for large-scale and metadata-hiding analytics over data streams.

Title: Succinct Zero-Knowledge Batch Proofs for Set Accumulators Abstract: ABSTRACTCryptographic accumulators are a common solution to proving information about a large set S. They allow one to compute a short digest of S and short certificates of some of its basic properties, notably membership of an element. Accumulators also allow one to track set updates: a new accumulator is obtained by inserting/deleting a given element. In this work we consider the problem of generating membership and update proofs for \em batches of elements so that we can succinctly prove additional properties of the elements (i.e., proofs are of constant size regardless of the batch size), and we can preserve privacy. Solving this problem would allow obtaining blockchain systems with improved privacy and scalability. The state-of-the-art approach to achieve this goal is to combine accumulators (typically Merkle trees) with zkSNARKs. This solution is however expensive for provers and does not scale for large batches of elements. In particular, there is no scalable solution for proving batch membership proofs when we require zero-knowledge (a standard definition of privacy-preserving protocols). In this work we propose new techniques to efficiently use zkSNARKs with RSA accumulators. We design and implement two main schemes: 1) \harisa, which proves batch membership in zero-knowledge; 2) \insarisa, which proves batch updates. For batch membership, the prover in \harisa is orders of magnitude faster than existing approaches based on Merkle trees (depending on the hash function). For batch updates we get similar cost savings compared to approaches based on Merkle trees; we also improve over the recent solution of Ozdemir et al. [USENIX'20].

Title: SFuzz: Slice-based Fuzzing for Real-Time Operating Systems Abstract: ABSTRACTReal-Time Operating System (RTOS) has become the main category of embedded systems. It is widely used to support tasks requiring real-time response such as printers and switches. The security of RTOS has been long overlooked as it was running in special environments isolated from attackers. However, with the rapid development of IoT devices, tremendous RTOS devices are connected to the public network. Due to the lack of security mechanisms, these devices are extremely vulnerable to a wide spectrum of attacks. Even worse, the monolithic design of RTOS combines various tasks and services into a single binary, which hinders the current program testing and analysis techniques working on RTOS. In this paper, we propose SFuzz, a novel slice-based fuzzer, to detect security vulnerabilities in RTOS. Our insight is that RTOS usually divides a complicated binary into many separated but single-minded tasks. Each task accomplishes a particular event in a deterministic way and its control flow is usually straightforward and independent. Therefore, we identify such code from the monolithic RTOS binary and synthesize a slice for effective testing. Specifically, SFuzz first identifies functions that handle user input, constructs call graphs that start from callers of these functions, and leverages forward slicing to build the execution tree based on the call graphs and pruning the paths independent of external inputs. Then, it detects and handles roadblocks within the coarse-grain scope that hinder effective fuzzing, such as instructions unrelated to the user input. And then, it conducts coverage-guided fuzzing on these code snippets. Finally, SFuzz leverages forward and backward slicing to track and verify each path constraint and determine whether a bug discovered in the fuzzer is a real vulnerability. SFuzz successfully discovered 77 zero-day bugs on 35 RTOS samples, and 67 of them have been assigned CVE or CNVD IDs. Our empirical evaluation shows that SFuzz outperforms the state-of-the-art tools (e.g., UnicornAFL) on testing RTOS.

Title: PSI from Ring-OLE Abstract: ABSTRACTPrivate set intersection (PSI) is one of the most extensively studied instances of secure computation. PSI allows two parties to compute the intersection of their input sets without revealing anything else. Other useful variants include PSI-Payload, where the output includes payloads associated with members of the intersection, and PSI-Sum, where the output includes the sum of the payloads instead of individual ones. In this work, we make two related contributions. First, we construct simple and efficient protocols for PSI and PSI-Payload from a ring version of oblivious linear function evaluation (ring-OLE) that can be efficiently realized using recent ring-LPN based protocols. A standard OLE over a field F allows a sender with a,b F to deliver ax + b to a receiver who holds x F. Ring-OLE generalizes this to a ring F, in particular, a polynomial ring over F. Our second contribution is an efficient general reduction of a variant of PSI-Sum to PSI-Payload and secure inner product. Our protocols have better communication cost than state-of-the-art PSI protocols, especially when requiring security against malicious parties and when allowing input-independent preprocessing. Compared to previous maliciously secure PSI protocols that have a similar computational cost, our online communication is 2x better for small sets (28-212 elements) and 20% better for large sets (220 -224). Our protocol is also simpler to describe and implement. We obtain even bigger improvements over the state of the art (4-5x better running time) for our variant of PSI-Sum.

Title: HammerScope: Observing DRAM Power Consumption Using Rowhammer Abstract: ABSTRACTThe constant reduction in memory cell sizes has increased memory density and reduced power consumption, but has also affected its reliability. The Rowhammer attack exploits this reduced reliability to induce bit flips in memory, without directly accessing these bits. Most Rowhammer attacks target software integrity, but some recent attacks demonstrated its use for compromising confidentiality. Continuing this trend, in this paper we observe that the \rh attack strongly correlates with the memory instantaneous power consumption. We exploit this observation to design HammerScope, a Rowhammer-based attack technique for measuring the power consumption of the memory unit. Because the power consumption correlates with the level of activity of the memory, \hs allows an attacker to infer memory activity. To demonstrate the offensive capabilities of HammerScope, we use it to mount three information leakage attacks. We first show that \hs can be used to break kernel address-space layout randomization (KASLR). Our second attack uses memory activity as a covert channel for a Spectre attack, allowing us to leak information from the operating system kernel. Finally, we demonstrate the use of HammerScope for performing website fingerprinting, compromising user privacy. Our work demonstrates the importance of finding systematic solutions for Rowhammer attacks.

Title: SortingHat: Efficient Private Decision Tree Evaluation via Homomorphic Encryption and Transciphering Abstract: ABSTRACTMachine learning as a service scenario typically requires the client to trust the server and provide sensitive data in plaintext. However, with the recent improvements in fully homomorphic encryption (FHE) schemes, many such applications can be designed in a privacy-preserving way. In this work, we focus on such a problem, private decision tree evaluation (PDTE) --- where a server has a decision tree classification model, and a client wants to use the model to classify her private data without revealing the data or the classification result to the server. We present an efficient non-interactive design of PDTE, that we call SortingHat, based on FHE techniques. As part of our design, we solve multiple cryptographic problems related to FHE: (1) we propose a fast homomorphic comparison function where one input can be in plaintext format; (2) we design an efficient binary decision tree evaluation technique in the FHE setting, which we call homomorphic traversal, and apply it together with our homomorphic comparison to evaluate private decision tree classifiers, obtaining running times orders of magnitude faster than the state of the art; (3) we improve both the communication cost and the time complexity of transciphering, by applying our homomorphic comparison to the FiLIP stream cipher. Through a prototype implementation, we demonstrate that our improved transciphering solution runs around 400 times faster than previous works. We finally present a choice in terms of PDTE design: we present a version of SortingHat without transciphering that achieves significant improvement in terms of computation cost compared to prior works, and another version t-SortingHat with transciphering that has a communication cost about 20 thousand times smaller but comparable running time.

Title: Sharp: Short Relaxed Range Proofs Abstract: ABSTRACTWe provide optimized range proofs, called Sharp, in discrete logarithm and hidden order groups, based on square decomposition. In the former setting, we build on the paradigm of Couteau et al. (Eurocrypt '21) and optimize their range proof (from now on, CKLR) in several ways: (1) We introduce batching via vector commitments and an adapted ∑;-protocol. (2) We introduce a new group switching strategy to reduce communication. (3) As repetitions are necessary to instantiate CKLR in standard groups, we provide a novel batch shortness test that allows for cheaper repetitions. The analysis of our test is nontrivial and forms a core technical contribution of our work. For example, for λ = 128 bit security and B = 64 bit ranges for N = 1 (resp. N = 8) proof(s), we reduce the proof size by 34% (resp. 75%) in arbitrary groups, and by 66% (resp. 88%) in groups of order 256-bit, compared to CKLR. As Sharp and CKLR proofs satisfy a "relaxed" notion of security, we show how to enhance their security with one additional hidden order group element. In RSA groups, this reduces the size of state of the art range proofs (Couteau et al., Eurocrypt '17) by 77% (λ = 128, B = 64, N = 1). Finally, we implement our most optimized range proof. Compared to the state of the art Bulletproofs (Bünz et al., S&P 2018), our benchmarks show a very significant runtime improvement. Eventually, we sketch some applications of our new range proofs.

Title: VRust: Automated Vulnerability Detection for Solana Smart Contracts Abstract: ABSTRACTSolana is a rapidly-growing high-performance blockchain powered by a Proof of History (PoH) consensus mechanism and a novel stateless programming model that decouples code from data. With parallel execution on the PoH Sealevel runtime (instead of PoW), it achieves 100X-1000X speedups compared to Ethereum in terms of transactions per second. With the new programming model, new constraints (owner, signer, keys, bump seeds) and vulnerabilities (missing checks, overflows, type confusion, etc.) must be carefully verified to ensure the security of Solana smart contracts. This paper proposes VRust, the first automated smart contract vulnerability detection framework for Solana. A key technical novelty is a set of static analysis rules for validating untrustful input accounts that are unique in the Solana programming model. We have developed a total of eight different vulnerability types, and VRust is able to check all of them fully automatically by translating source code into Rust MIR-based inference rules without any code annotations. VRust has been evaluated on over a hundred of Solana projects, and it has revealed 12 previously unknown vulnerabilities, including 3 critical vulnerabilities in the official Solana Programming Library confirmed by core developers.

Title: Two-Client Inner-Product Functional Encryption with an Application to Money-Laundering Detection Abstract: ABSTRACTIn this paper, we extend Inner-Product Functional Encryption (IPFE), where there is just a vector in the key and a vector in the single sender's ciphertext, to two-client ciphertexts. More precisely, in our two-client functional encryption scheme, there are two Data Providers who can independently encrypt vectors x and y for a data consumer who can, from a functional decryption key associated to a vector α, compute ∑αi xiyi = x ⋅ Diag(α) ⋅ yT. Ciphertexts are linear in the dimension of the vectors, whereas the functional decryption keys are of constant size. We study two interesting particular cases: 2-party Inner-Product Functional Encryption, with α = (1,…,1). There is a unique functional decryption key, which enables the computation of x ⋅ xT by a third party, where x and y are provided by two independent clients;Inner-Product Functional Encryption with a Selector, with x = x0 II x1 and y = bn II bn ∈{1n || 0n, 0n II 1n}, for some bit b, on the public coefficients α = α0 II α1, in the functional decryption key, so that one gets xb ⋅ αbT, where x and b are provided by two independent clients. This result is based on the fundamental Product-Preserving Lemma, which is of independent interest. It exploits Dual Pairing Vector Spaces (DPVS), with security proofs under the SXDH assumption. We provide two practical applications to medical diagnosis for the latter IPFE with a selector, and to money-laundering detection for the former 2-party IPFE, both with strong privacy properties, adaptative security and the use of labels granting a Multi-Client Functional Encryption (MCFE) security for the scheme, thus enabling its use in practical situations.

Title: On the (In)Security of Secure ROS2 Abstract: ABSTRACTRobot Operating System (ROS) has been the mainstream platform for research and development of robotic applications. This platform is well-known for lacking security features and efficiency for distributed robotic computations. To address these issues, ROS2 is recently developed by utilizing the Data Distribution Service (DDS) to provide security support. Integrated with DDS, ROS2 is expected to establish the basis for trustworthy robotic ecosystems. In this paper, we systematically study the security of the current ROS2 implementation from three perspectives. By abstracting the key functions from the ROS2 native implementation, we first formally describe the ROS2 system communication workflow and model it using a concurrent modeling language. Second, we verify the model with some key security properties through a model checker, and successfully identify four security vulnerabilities in ROS2's native security module: Secure ROS2 (SROS2). To validate these flaws, we set up simulation and physical multi-robot testbeds running different real-world workloads developed by Open Robotics and Amazon AWS Robotics. We demonstrate that an adversary can exploit these vulnerabilities to totally invalidate the security protection offered by SROS2, and obtain unauthorized permissions or steal critical information. Third, to enhance the security of ROS2, we propose a general defense solution based on the private broadcast encryption scheme. We run different workloads and benchmarks to show the efficiency and security of our defense. Our findings have been acknowledge by ROS2 official, and the suggested mitigation has been implemented in the latest SROS2 version.

Title: FenceSitter: Black-box, Content-Agnostic, and Synchronization-Free Enrollment-Phase Attacks on Speaker Recognition Systems Abstract: ABSTRACTSpeaker Recognition Systems (SRSs) grant access to legitimate users based on voiceprint. Recent research has shown that SRSs can be bypassed during the training phase (backdoor attacks) and the recognition phase (evasion attacks). In this paper, we explore a new attack surface of SRSs by presenting an enrollment-phase attack paradigm, named FenceSitter, where the adversary poisons the SRS using imperceptible adversarial ambient sound when the legitimate user registers into the SRS. The tainted voiceprint extracted by the SRS allows both the adversary and the legitimate user to access the system in all future recognition phases. To materialize such attack, we interleave carefully-designed continuous adversarial perturbations into innocent-sounding ambient sound. As computing adversarial perturbations over a long sequence of ambient sound carrier is intractable, we optimize over adversarial segments with content desensitization and physical realization. In addition, the attack is made available under the black-box settings by gradient estimation based on the natural evolution strategy. Extensive experiments have been conducted on both English and Chinese voice datasets for close-set identification (CSI), open-set identification (OSI), and speaker verification (SV) tasks. The results under various digital and physical conditions have verified the effectiveness and robustness of FenceSitter. With live enrollment experiments and user study, we further validate the practicality of FenceSitter. Our work reveals the vulnerability of SRSs during the enrollment phase, which may spur future research in improving the security of SRSs.

Title: StrongBox: A GPU TEE on Arm Endpoints Abstract: ABSTRACTA wide range of Arm endpoints leverage integrated and discrete GPUs to accelerate computation such as image processing and numerical processing applications. However, in spite of these important use cases, Arm GPU security has yet to be scrutinized by the community. By exploiting vulnerabilities in the kernel, attackers can directly access sensitive data used during GPU computing, such as personally-identifiable image data in computer vision tasks. Existing work has used Trusted Execution Environments (TEEs) to address GPU security concerns on Intel-based platforms, while there are numerous architectural differences that lead to novel technical challenges in deploying TEEs for Arm GPUs. In addition, extant Arm-based GPU defenses are intended for secure machine learning, and lack generality. There is a need for generalizable and efficient Arm-based GPU security mechanisms. To address these problems, we present StrongBox, the first GPU TEE for secured general computation on Arm endpoints. During confidential computation on Arm GPUs, StrongBox provides an isolated execution environment by ensuring exclusive access to the GPU. Our approach is based in part on a dynamic, fine-grained memory protection policy as Arm-based GPUs typically share a unified memory with the CPU, a stark contrast with Intel-based platforms. Furthermore, by characterizing GPU buffers as secure and non-secure, StrongBox reduces redundant security introspection operations to control access to sensitive data used by the GPU, ultimately reducing runtime overhead. Our design leverages the widely-deployed Arm TrustZone and generic Arm features, without hardware modification or architectural changes. We prototype StrongBox using an off-the-shelf Arm Mali GPU and perform an extensive evaluation. Our results show that StrongBox successfully ensures the GPU computing security with a low (4.70% - 15.26%) overhead across several indicative benchmarks.

Title: A Run a Day Won't Keep the Hacker Away: Inference Attacks on Endpoint Privacy Zones in Fitness Tracking Social Networks Abstract: ABSTRACTFitness tracking social networks such as Strava allow users to record sports activities and share them publicly. Sharing encourages peer interaction but also constitutes a risk, because an activity's start or finish may inadvertently reveal privacy-sensitive locations such as a home or workplace. To mitigate this risk, networks introduced endpoint privacy zones (EPZs), which hide track portions around protected locations. In this paper, we show that EPZ implementations of major services remain vulnerable to inference attacks that significantly reduce the effective anonymity provided by the EPZ, and even reveal the protected location. Our attack leverages distance information leaked in activity metadata, street grid data, and the locations of the entry points into the EPZ. This yields a constrained search space where we use regression analysis to predict protected locations. Our evaluation on 1.4 million Strava activities shows that our attack discovers the protected location for up to 85% of EPZs. Larger EPZs reduce the performance of our attack, while geographically dispersed activities in sparser street grids yield better performance. We propose six countermeasures, that, however, come with a usability trade-off, and responsibly disclosed our findings and countermeasures to the major networks.

Title: Second-Order Low-Randomness d + 1 Hardware Sharing of the AES Abstract: ABSTRACTIn this paper, we introduce a second-order masking of the AES using the minimal number of shares and a total of 1268 bits of randomness including the sharing of the plaintext and key. The masking of the S-box is based on the tower field decomposition of the inversion over bytes where the changing of the guards technique is used in order to re-mask the middle branch of the decomposition. The sharing of the S-box is carefully crafted such that it achieves first-order probing security without the use of randomness and such that the sharing of its output is uniform. Multi-round security is achieved by re-masking the state where we use a theoretical analysis based on the propagation of probed information to reduce the demand for fresh randomness per round. The result is a second-order masked AES which competes with the state-of-the-art in terms of latency and area, but reduces the randomness complexity over eight times over the previous known works. In addition to the corresponding theoretical analysis and proofs for the security of our masked design, it has been implemented on FPGA and evaluated via lab analysis.

Title: Improving Line-Point Zero Knowledge: Two Multiplications for the Price of One Abstract: ABSTRACTRecent advances in fast protocols for vector oblivious linear evaluation (VOLE) have inspired a family of new VOLE-based lightweight designated-verifier NIZK protocols (Weng et al., S&P 2021, Baum et al., Crypto 2021, Dittmer et al., ITC 2021, Yang et al., CCS 2021). In particular, the Line-Point Zero Knowledge (LPZK) protocol of Dittmer et al. has the advantage of being entirely non-cryptographic given a single instance of a random VOLE correlation. We present improvements to LPZK through the introduction of additional structure to the correlated randomness. Using an efficiently realizable variant of the VOLE correlation, we reduce the online proof size of LPZK by roughly 2x: from roughly 2 field elements per multiplication gate, or 1 element in the random oracle variant, to only 1 or 1/2 elements respectively. In particular, we get the first practical VOLE-based NIZK that breaks the 1-element-per-multiplication barrier. We implemented an optimized version of our protocol and compared it with other recent VOLE-based NIZK protocols. In the typical case where communication is the bottleneck, we get at least 2x performance improvement over all previous VOLE-based protocols. When prover computation is the bottleneck, we outperform all non-LPZK protocols by at least 2-3x and (our optimized implementation of) LPZK by roughly 30%, obtaining a 2-3x slowdown factor compared to plain circuit evaluation.

Title: Shorter Signatures Based on Tailor-Made Minimalist Symmetric-Key Crypto Abstract: ABSTRACTSignature schemes based on the MPC-in-the-head approach (MPCitH) have either been designed by taking a proof system and selecting a suitable symmetric-key primitive (Picnic, CCS16), or starting with an existing primitive such as AES and trying to find the most suitable proof system (BBQ, SAC19 or Banquet, PKC21). In this work we do both: we improve certain symmetric-key primitives to better fit existing signature schemes, and we also propose a new signature scheme that combines a new, minimalist one-way function with changes to a proof system to make their combination even more efficient. Our concrete results are as follows. First, we show how to provably remove the need to include the key schedule of block ciphers. This simplifies schemes like Picnic and it also leads to the fastest and smallest AES-based signatures, where we achieve signature sizes of around 10.8 to 14.2 KB using AES-128, on average 10% shorter than Banquet and 15% faster. Second, we investigate a variant of AES with larger S-boxes we call LSAES, for which we argue that it is likely to be at least as strong as AES, further reducing the size of AES-based signatures to 9.9 KB. Finally, we present a new signature scheme, Rainier, combining a new one-way function called Rain with a Banquet-like proof system. To the best of our knowledge, it is the first MPCitH-based signature scheme which can produce signatures that are less than 5 KB in size; it also outperforms previous Picnic and Banquet instances in all performance metrics.

Title: Leakage and Tamper Resilient Permutation-Based Cryptography Abstract: ABSTRACTImplementation attacks such as power analysis and fault attacks have shown that, if potential attackers have physical access to a cryptographic device, achieving practical security requires more considerations apart from just cryptanalytic security. In recent years, and with the advent of micro-architectural or hardware-oriented attacks, it became more and more clear that similar attack vectors can also be exploited on larger computing platforms and without the requirement of physical proximity of an attacker. While newly discovered attacks typically come with implementation recommendations that help counteract a specific attack vector, the process of constantly patching cryptographic code is quite time consuming in some cases, and simply not possible in other cases. What adds up to the problem is that the popular approach of leakage resilient cryptography only provably solves part of the problem: it discards the threat of faults. Therefore, we put forward the usage of leakage and tamper resilient cryptographic algorithms, as they can offer built-in protection against various types of physical and hardware oriented attacks, likely including attack vectors that will only be discovered in the future. In detail, we present the - to the best of our knowledge - first framework for proving the security of permutation-based symmetric cryptographic constructions in the leakage and tamper resilient setting. As a proof of concept, we apply the framework to a sponge-based stream encryption scheme called asakey and provide a practical analysis of its resistance against side channel and fault attacks.

Title: Exposing the Rat in the Tunnel: Using Traffic Analysis for Tor-based Malware Detection Abstract: ABSTRACTTor~\citetor is the most widely used anonymous communication network with millions of daily users~\citetormetrics. Since Tor provides server and client anonymity, hundreds of malware binaries found in the wild rely on it to hide their presence and hinder Command & Control (C&C) takedown operations. We believe Tor is a paramount tool enabling online freedom and privacy, and blocking it to defend against such malware is infeasible for both users and organizations. In this work, we present effective traffic analysis approaches that can accurately identify Tor-based malware communication. We collect hundreds of Tor-based malware binaries, execute and examine more than 47,000 active encrypted malware connections and compare them with benign browsing traffic. In addition to traditional traffic analysis features (which work at the connection level), we propose global host-level network features to capture peculiar malware communication fingerprints across host logs. Our experiments confirm that our models are able to detect "zero-day'' malware connections with 0.7% FPR even when malware connections constitute less than 5% of Tor traces in the test set. Using multi-labeling approaches, we are able to accurately detect the malware behavior-based classes (grayware, ransomware, etc). Finally, we evaluate the robustness of our models on real-world enterprise logs and show that the classifiers can identify infected hosts even with missing features.

Title: Watch Out for Race Condition Attacks When Using Android External Storage Abstract: ABSTRACTCurrently, in Android, applications (apps for short) rely heavily on external storage to provide their services. Race conditions are introduced by the inappropriate file operations. Through race conditions, the malicious app can manipulate the file content and induce the victim app to perform unexpected actions, which we callrace condition attack. Race condition attack can cause a series of security problems and prior work has already implemented some of them. From Android 10, Google has introduced scoped storage to defend against attacks based on external storage. However, considering current market shares of different Android versions, it is still a long way to have scoped storage deployed on each device. To protect current users from this kind of attack, it is essential to raise app developers' security awareness. Therefore, we conduct a comprehensive survey on race condition attack to learn about its current status over Android apps. We propose an analysis engine, named RECAST, which gathers file operation events on external storage and infers the associated file operation processes. With RECAST, we collect 5,359,339 file operation events over 105,963 files. From the analysis result, we find that, with the limited kinds of events, a tremendous number of unique file operating patterns (1,977) are constituted. Over these file operating patterns, the time window is much common and available to launch a series of attacks (94.26% of the tested files are vulnerable to this problem). Consequently, race condition attack has become a non-negligible issue for app developers when using Android external storage.

Title: Towards Automated Safety Vetting of Smart Contracts in Decentralized Applications Abstract: ABSTRACTWe propose VetSC, a novel UI-driven, program analysis guided model checking technique that can automatically extract contract semantics in DApps so as to enable targeted safety vetting. To facilitate model checking, we extract business model graphs from contract code that capture its intrinsic business and safety logic. To automatically determine what safety specifications to check, we retrieve textual semantics from DApp user interfaces. To exclude untrusted UI text, we also validate the UI-logic consistency and detect any discrepancies. We have implemented VetSC and applied it to 34 real-world DApps. Experiments have demonstrated that VetSC can accurately interpret smart contract code, enable autonomous safety vetting, and discover safety risks in real-world Dapps. Using our tool, we have successfully discovered 19 new safety risks in the wild, such as expired lottery tickets and double voting.

Title: Poirot: Probabilistically Recommending Protections for the Android Framework Abstract: ABSTRACTInconsistent security policy enforcement within the Android framework can allow malicious actors to improperly access sensitive resources. A number of prominent inconsistency detection approaches have been proposed in and across various layers of the Android operating system. However, the existing approaches suffer from high false positive rates as they rely solely on simplistic convergence analysis and reachability based relations to reason about the validity of access control enforcement. We observe that resource-to-access control associations are highly uncertain in the context of Android. Thus, we introduce Poirot, a next-generation inconsistency detection tool that leverages probabilistic inference to generate a comprehensive set of protection recommendations for Android framework APIs. We evaluate Poirot on four Android images and detect 26 total inconsistencies.

Title: TurboPack: Honest Majority MPC with Constant Online Communication Abstract: ABSTRACTWe present a novel approach to honest majority secure multiparty computation in the preprocessing model with information theoretic security that achieves the best online communication complexity. The online phase of our protocol requires 12 elements in total per multiplication gate with circuit-dependent preprocessing, or 20 elements in total with circuit-independent preprocessing. Prior works achieved linear online communication complexity in n, the number of parties, with the best prior existing solution involving 1.5n elements per multiplication gate. Only one recent work packing [28] achieves constant online communication complexity, but the constants are large (108 elements for passive security, and twice that for active security). That said, our protocol offers a very efficient information theoretic online phase for any number of parties. The total end-to-end communication cost with the preprocessing phase is linear in n, i.e., 10n + 44, which is larger than the 4n complexity of the state-of-the-art protocols. The gap is not significant when the online phase must be optimized as a priority and a reasonably large number of parties is involved. Unlike previous works based on packed secret-sharing to reduce communication complexity, we further reduce the communication by avoiding the use of complex and expensive network routing or permutations tools. Furthermore, we also allow for a maximal honest majority adversary, while most previous works require the set of honest parties to be strictly larger than a majority. Our protocol is simple and offers concrete efficiency. To illustrate this we present a full-fledged implementation together with experimental results that show improvements in online phase runtimes that go up to 5x in certain settings (e.g. 45 parties, LAN network, circuit of depth 10 with 1M gates).

Title: When Frodo Flips: End-to-End Key Recovery on FrodoKEM via Rowhammer Abstract: ABSTRACTIn this work, we recover the private key material of the FrodoKEM key exchange mechanism as submitted to the NIST Post Quantum Cryptography (PQC) standardization process. The new mechanism that allows for this is a Rowhammer-assisted poisoning of the FrodoKEM Key Generation (KeyGen) process. The Rowhammer side-channel is a hardware-based security exploit that allows flipping bits in DRAM by "hammering" rows of memory adjacent to some target-victim memory location by repeated memory accesses. Using Rowhammer, we induce the FrodoKEM software to output a higher-error Public Key (PK), (\matA, \matB = \matA \matS +\vec\widetildeE ), where the error \widetilde\vecE is modified by Rowhammer. Then, we perform a decryption failure attack, using a variety of publicly-accessible supercomputing resources running on the order of only 200,000 core-hours. We delicately attenuate the decryption failure rate to ensure that the adversary's attack succeeds practically, but so honest users cannot easily detect the manipulation. Achieving this public key "poisoning'' requires an extreme engineering effort, as FrodoKEM's KeyGen runs on the order of 8 milli seconds. (Prior Rowhammer-assisted attacks against cryptography require as long as 8 hours of persistent access.) In order to handle this real-world timing condition, we require a wide variety of prior and brand new, low-level engineering techniques, including e.g. memory massaging algorithms -- i.e. "Feng Shui'' -- and a precisely-targeted performance degradation attack on the extendable output function SHAKE. We explore the applicability of our techniques to other lattice-based KEMs in the NIST PQC Round 3 candidate-pool, e.g. Kyber, Saber, etc, as well as the difficulties that arise in the various settings. To conclude, we discuss various simple countermeasures to protect implementations against this, and similar, attacks.

Title: Shifted Inverse: A General Mechanism for Monotonic Functions under User Differential Privacy Abstract: ABSTRACTWhile most work on differential privacy has focused on protecting the privacy of tuples, it has been realized that such a simple model cannot capture the complex user-tuple relationships in many real-world applications. Thus, user differential privacy (user-DP) has recently gained more attention, which includes node-DP for graph data as a special case. Most existing work on user-DP has only studied the sum estimation problem. In this work, we design a general DP mechanism for any monotonic function under user-DP with strong optimality guarantees. While our general mechanism may run in super-polynomial time, we show how to instantiate an approximate version in polynomial time on some common monotonic functions, including sum, k-selection, maximum frequency, and distinct count. Finally, we conduct experiments on all these functions and the results show that our framework is more general and obtains better results in many cases.

Title: CINI MINIS: Domain Isolation for Fault and Combined Security Abstract: ABSTRACTObservation and manipulation of physical characteristics are well-known and powerful threats to cryptographic devices. While countermeasures against passive side-channel and active fault-injection attacks are well understood individually, combined attacks, i.e., the combination of fault injection and side-channel analysis, is a mostly unexplored area. Naturally, the complexity of analysis and secure construction increases with the sophistication of the adversary, making the combined scenario especially challenging. To tackle complexity, the side-channel community has converged on the construction of small building blocks, which maintain security properties even when composed. In this regard, Probe-Isolating Non-Interference (PINI) is a widely used notion for secure composition in the presence of side-channel attacks due to its efficiency and elegance. In this work, we transfer the core ideas behind PINI to the context of fault and combined security and, from that, construct the first trivially composable gadgets in the presence of a combined adversary.

Title: Adversarial Correctness and Privacy for Probabilistic Data Structures Abstract: ABSTRACTWe study the security of Probabilistic Data Structures (PDS) for handling Approximate Membership Queries (AMQ); prominent examples of AMQ-PDS are Bloom and Cuckoo filters. AMQ-PDS are increasingly being deployed in environments where adversaries can gain benefit from carefully selecting inputs, for example to increase the false positive rate of an AMQ-PDS. They are also being used in settings where the inputs are sensitive and should remain private in the face of adversaries who can access an AMQ-PDS through an API or who can learn its internal state by compromising the system running the AMQ-PDS. We develop simulation-based security definitions that speak to correctness and privacy of AMQ-PDS. Our definitions are general and apply to a broad range of adversarial settings. We use our definitions to analyse the behaviour of both Bloom filters and insertion-only Cuckoo filters. We show that these AMQ-PDS can be provably protected through replacement or composition of hash functions with keyed pseudorandom functions in their construction. We also examine the practical impact on storage size and computation of providing secure instances of Bloom and insertion-only Cuckoo filters.

Title: LibAFL: A Framework to Build Modular and Reusable Fuzzers Abstract: ABSTRACTThe release of AFL marked an important milestone in the area of software security testing, revitalizing fuzzing as a major research topic and spurring a large number of research studies that attempted to improve and evaluate the different aspects of the fuzzing pipeline. Many of these studies implemented their techniques by forking the AFL codebase. While this choice might seem appropriate at first, combining multiple forks into a single fuzzer requires a high engineering overhead, which hinders progress in the area and prevents fair and objective evaluations of different techniques. The highly fragmented landscape of the fuzzing ecosystem also prevents researchers from combining orthogonal techniques and makes it difficult for end users to adopt new prototype solutions. To tackle this problem, in this paper we propose LibAFL, a framework to build modular and reusable fuzzers. We discuss the different components generally used in fuzzing and map them to an extensible framework. LibAFL allows researchers and engineers to extend the core fuzzer pipeline and share their new components for further evaluations. As part of LibAFL, we integrated techniques from more than 20 previous works and conduct extensive experiments to show the benefit of our framework to combine and evaluate different approaches. We hope this can help to shed light on current advancements in fuzzing and provide a solid base for comparative and extensible research in the future.

Title: Squirrel: Efficient Synchronized Multi-Signatures from Lattices Abstract: ABSTRACTThe focus of this work are multi-signatures schemes in the synchronized setting. A multi-signature scheme allows multiple signatures for the same message but from independent signers to be compressed into one short aggregated signature, which allows verifying all of the signatures simultaneously. In the synchronized setting, the signing algorithm takes the current time step as an additional input. It is assumed that no signer signs more than one message per time step and we aim to aggregate signatures for the same message and same time step. This setting is particularly useful in the context of blockchains, where validators are naturally synchronized by the blocks they sign. We present Squirrel, a concretely efficient lattice-based multi-signature scheme in the synchronized setting that works for a bounded number of 2τ time steps and allows for aggregating up to ρ signatures at each step, where both τ and ρ are public parameters upon which the efficiency of our scheme depends. Squirrel allows for non-interactive aggregation of independent signatures and is proven secure in the random oracle model in the presence of rogue-key attacks assuming the hardness of the short integer solution problem in a polynomial ring. We provide a careful analysis of all parameters and show that Squirrel can be instantiated with good concrete efficiency. For τ = 24 and ρ = 4096, a signer could sign a new message every 10 seconds for 5 years non-stop. Assuming the signer has a cache of 112 MB, signing takes 68 ms and verification of an aggregated signature takes 36 ms. The size of the public key is 1 KB, the size of an individual signature is 52 KB, and the size of an aggregated signature is 771 KB.

Title: Secure Auctions in the Presence of Rational Adversaries Abstract: ABSTRACTSealed bid auctions are used to allocate a resource among a set of interested parties. Traditionally, auctions need the presence of a trusted auctioneer to whom the bidders provide their private bid values. Existence of such a trusted party is not an assumption easily realized in practice. Generic secure computation protocols can be used to remove a trusted party. However, generic techniques result in inefficient protocols, and typically do not provide fairness -- that is, a corrupt party can learn the output and abort the protocol thereby preventing other parties from learning the output. At CRYPTO 2009, Miltersen, Nielsen and Triandopoulos~\citeC:MilNieTri09, introduced the problem of building auctions that are secure against rational bidders. Such parties are modeled as self-interested agents who care more about maximizing their utility than about learning information about bids of other agents. To realize this, they put forth a novel notion of information utility and introduce a game-theoretic framework that helps analyse protocols while taking into account both information utility as well as monetary utility. Unfortunately, their construction makes use a of generic MPC protocol and, consequently, the authors do not analyze the concrete efficiency of their protocol. In this work, we construct the first concretely efficient and provably secure protocol for First Price Auctions in therational setting. Our protocol guarantees privacy, public verifiability and fairness. Inspired by~\citeC:MilNieTri09, we put forth a solution concept that we callPrivacy Enhanced Computational Weakly Dominant Strategy Equilibrium that captures parties' privacy and monetary concerns in the game theoretic context, and show that our protocol realizes this. We believe this notion to be of independent interest. Our protocol is crafted specifically for the use case of auctions, is simple, using off-the-shelf cryptographic components. Executing our auction protocol on commodity hardware with 30 bidders, with bids of length 10, our protocol runs to completion in 0.429s and has total communication of 82KB.

Title: Succinct Zero Knowledge for Floating Point Computations Abstract: ABSTRACTWe study the problem of constructing succinct zero knowledge proof systems for floating point computations. The standard approach to handle floating point computations requires conversion to binary circuits, following the IEEE-754 floating point standard. This approach incurs a poly(w) overhead in prover efficiency for computations with w-bit precision, resulting in very high prover runtimes -- already the key bottleneck in the design of succinct arguments. We make the following contributions: -We propose a new model for verifying floating point computations that guarantees approximate correctness w.r.t. a relative error bound. This model is inspired by numerical analysis, and is very meaningful for applications such as machine learning and scientific computing. -Using this model, we present a general method for constructing succinct zero-knowledge proofs for floating point computations starting from existing public-coin "commit-and-prove'' systems. For computations with w-bit precision, our approach incurs only a log(w) overhead in prover running time. Our compiler nearly preserves (up to a factor of 2) the communication complexity of the underlying protocol, and requires sub-linear verification time. The resulting proof can be made non-interactive in the random oracle model. Concretely, our scheme is ~57x faster than the method following IEEE standard exactly [35] for 32-bit floating point computations. Central to our main result, and of independent interest, is a new batch range proof system in standard prime order groups that does not rely on bit decomposition.

Title: Practical Settlement Bounds for Proof-of-Work Blockchains Abstract: ABSTRACTNakamoto proof-of-work ledger consensus currently underlies the majority of deployed cryptocurrencies and smart-contract blockchains. While a long and fruitful line of work has succeeded to identify its exact security region---that is, the set of parametrizations under which it possesses asymptotic security---the existing theory does not provide concrete settlement time guarantees that are tight enough to inform practice. In this work we provide a new approach for obtaining concrete and practical settlement time guarantees suitable for reasoning about deployed systems. We give an efficient method for computing explicit upper bounds on settlement time as a function of primary system parameters: honest and adversarial computational power and a bound on network delays. We implement this computational method and provide a comprehensive sample of concrete bounds for several settings of interest. We also analyze a well-known attack strategy to provide lower bounds on the settlement times. For Bitcoin, for example, our upper and lower bounds are within 90 seconds of each other for 1-hour settlement assuming 10 second network delays and a 10% adversary. In comparison, the best prior result has a gap of 2 hours in the upper and lower bounds with the same parameters.

Title: C2C: Fine-grained Configuration-driven System Call Filtering Abstract: ABSTRACTConfiguration options allow users to customize application features according to the desired requirements. While the code that corresponds to disabled features is never executed, it still resides in process memory and comprises part of the application's attack surface, e.g., it can be reused for the construction of exploit code. Automatically reducing the attack surface of disabled application features according to a given configuration is thus a desirable defense-in-depth capability. The intricacies of modern software design and the complexities of popular programming languages, however, introduce significant challenges in automatically deriving the mapping of configuration options to their corresponding application code. In this paper, we present Configuration-to-Code (C2C), a generic configuration-driven attack surface reduction technique that automatically maps configuration options to application code using static code analysis and instrumentation. C2C operates at a fine-grained level by pruning configuration-dependent conditional branches in the control flow graph, allowing the precise identification of a given configuration option's code at the basic block level. At runtime, C2C reduces the application's attack surface by filtering any system calls required exclusively by disabled features. Using popular applications, we show how security-critical system calls (such as execve) can be automatically disabled when not needed, limiting an attacker's vulnerability exploitation capabilities. System call filtering also reduces the exposed attack surface of the underlying Linux kernel, neutralizing 32 additional CVEs (for a total of 88) compared to previous software specialization techniques.

Title: Foundations of Coin Mixing Services Abstract: ABSTRACTCoin mixing services allow users to mix their cryptocurrency coins and thus enable unlinkable payments in a way that prevents tracking of honest users' coins by both the service provider and the users themselves. The easy bootstrapping of new users and backwards compatibility with cryptocurrencies (such as Bitcoin) with limited support for scripts are attractive features of this architecture, which has recently gained considerable attention in both academia and industry. A recent work of Tairi et al. [IEEE S&P 2021] formalizes the notion of a coin mixing service and proposes A2L, a new cryptographic protocol that simultaneously achieves high efficiency and interoperability. In this work, we identify a gap in their formal model and substantiate the issue by showing two concrete counterexamples: we show how to construct two encryption schemes that satisfy their definitions but lead to a completely insecure system. To amend this situation, we investigate secure constructions of coin mixing services. First, we develop the notion of blind conditional signatures (BCS), which acts as the cryptographic core for coin mixing services. We propose game-based security definitions for BCS and propose A2L+, a modified version of the protocol by Tairi et al. that satisfies our security definitions. Our analysis is in an idealized model (akin to the algebraic group model) and assumes the hardness of the one-more discrete logarithm problem. Finally, we propose A2L-UC, another construction of BCS that achieves the stronger notion of UC-security (in the standard model), albeit with a significant increase in computation cost. This suggests that constructing a coin mixing service protocol secure under composition requires more complex cryptographic machinery than initially thought.

Title: Watch Your Back: Identifying Cybercrime Financial Relationships in Bitcoin through Back-and-Forth Exploration Abstract: ABSTRACTCybercriminals often leverage Bitcoin for their illicit activities. In this work, we propose back-and-forth exploration, a novel automated Bitcoin transaction tracing technique to identify cybercrime financial relationships. Given seed addresses belonging to a cybercrime campaign, it outputs a transaction graph, and identifies paths corresponding to relationships between the campaign under study and external services and other cybercrime campaigns. Back-and-forth exploration provides two key contributions. First, it explores both forward and backwards, instead of only forward as done by prior work, enabling the discovery of relationships that cannot be found by only exploring forward (e.g., deposits from clients of a mixer). Second, it prevents graph explosion by combining a tagging database with a machine learning classifier for identifying addresses belonging to exchanges. We evaluate back-and-forth exploration on 30 malware families. We build oracles for 4 families using Bitcoin for C&C and use them to demonstrate that back-and-forth exploration identifies 13 C&C signaling addresses missed by prior work, 8 of which are fundamentally missed by forward-only explorations. Our approach uncovers a wealth of services used by the malware including 44 exchanges, 11 gambling sites, 5 payment service providers, 4 underground markets, 4 mining pools, and 2 mixers. In 4 families, the relations include new attribution points missed by forward-only explorations. It also identifies relationships between the malware families and other cybercrime campaigns, highlighting how some malware operators participate in a variety of cybercriminal activities.

Title: DangZero: Efficient Use-After-Free Detection via Direct Page Table Access Abstract: ABSTRACTUse-after-free vulnerabilities remain difficult to detect and mitigate, making them a popular source of exploitation. Existing solutions incur impractical performance/memory overhead, require specialized hardware, and/or guarantee only protection, but not detection. In this paper, we propose DangZero, a new solution to detect use-after-free vulnerabilities as they occur. DangZero builds on a traditional page protection and aliasing scheme, where objects are made inaccessible after a free, and subsequent accesses are immediately detected. In contrast to prior solutions using alias-based detection, DangZero relies on direct page table access in ring 0 to provide a much more efficient implementation. The key idea is that, by giving the program's allocator direct access to the page tables, we can efficiently manage and invalidate vulnerable objects. To safely implement this, we build upon a unikernel-like design, where virtualization provides ring-0 (guest-mode) access, isolation, as well as compatibility with existing Linux programs. Moreover, we show direct page table access serves as an efficient building block for garbage collection-style alias reclaiming. Doing so provides the ability to safely reuse freed areas and address the scalability issues plaguing state-of-the-art alias-based solutions. Our experimental results confirm that DangZero provides accurate detection guarantees with significantly lower overhead than competing state-of-the-art solutions (e.g., 18% saturated throughput degradation on long-running programs such as the Nginx web server).

Title: Proof-of-Possession for KEM Certificates using Verifiable Generation Abstract: ABSTRACTCertificate authorities in public key infrastructures typically require entities to prove possession of the secret key corresponding to the public key they want certified. While this is straightforward for digital signature schemes, the most efficient solution for public key encryption and key encapsulation mechanisms (KEMs) requires an interactive challenge-response protocol, requiring a departure from current issuance processes. In this work we investigate how to non-interactively prove possession of a KEM secret key, specifically for lattice-based KEMs, motivated by the recently proposed KEMTLS protocol which replaces signature-based authentication in TLS 1.3 with KEM-based authentication. Although there are various zero-knowledge (ZK) techniques that can be used to prove possession of a lattice key, they yield large proofs or are inefficient to generate. We propose a technique called verifiable generation, in which a proof of possession is generated at the same time as the key itself is generated. Our technique is inspired by the Picnic signature scheme and uses the multi-party-computation-in-the-head (MPCitH) paradigm; this similarity to a signature scheme allows us to bind attribute data to the proof of possession, as required by certificate issuance protocols. We show how to instantiate this approach for two lattice-based KEMs in Round 3 of the NIST post-quantum cryptography standardization project, Kyber and FrodoKEM, and achieve reasonable proof sizes and performance. Our proofs of possession are faster and an order of magnitude smaller than the previous best MPCitH technique for knowledge of a lattice key, and in size-optimized cases can be comparable to even state-of-the-art direct lattice-based ZK proofs for Kyber. Our approach relies on a new result showing the uniqueness of Kyber and FrodoKEM secret keys, even if the requirement that all secret key components are small is partially relaxed, which may be of independent interest for improving efficiency of zero-knowledge proofs for other lattice-based statements.

Title: SPECPATCH: Human-In-The-Loop Adversarial Audio Spectrogram Patch Attack on Speech Recognition Abstract: ABSTRACTIn this paper, we propose SpecPatch, a human-in-the loop adversarial audio attack on automated speech recognition (ASR) systems. Existing audio adversarial attacker assumes that the users cannot notice the adversarial audios, and hence allows the successful delivery of the crafted adversarial examples or perturbations. However, in a practical attack scenario, the users of intelligent voice-controlled systems (e.g., smartwatches, smart speakers, smartphones) have constant vigilance for suspicious voice, especially when they are delivering their voice commands. Once the user is alerted by a suspicious audio, they intend to correct the falsely-recognized commands by interrupting the adversarial audios and giving more powerful voice commands to overshadow the malicious voice. This makes the existing attacks ineffective in the typical scenario when the user's interaction and the delivery of adversarial audio coincide. To truly enable the imperceptible and robust adversarial attack and handle the possible arrival of user interruption, we design SpecPatch, a practical voice attack that uses a sub-second audio patch signal to deliver an attack command and utilize periodical noises to break down the communication between the user and ASR systems. We analyze the CTC (Connectionist Temporal Classification) loss forwarding and backwarding process and exploit the weakness of CTC to achieve our attack goal. Compared with the existing attacks, we extend the attack impact length (i.e., the length of attack target command) by 287%. Furthermore, we show that our attack achieves 100% success rate in both over-the-line and over-the-air scenarios amid user intervention.

Title: Location Heartbleeding: The Rise of Wi-Fi Spoofing Attack Via Geolocation API Abstract: ABSTRACTLocation spoofing attack deceiving a Wi-Fi positioning system has been studied for over a decade. However, it has been challenging to construct a practical spoofing attack in urban areas with dense coverage of legitimate Wi-Fi APs. This paper identifies the vulnerability of the Google Geolocation API, which returns the location of a mobile device based on the information of the Wi-Fi access points that the device can detect. We show that this vulnerability can be exploited by the attacker to reveal the black-box localization algorithms adopted by the Google Wi-Fi positioning system and easily launch the location spoofing attack in dense urban areas with a high success rate. Furthermore, we find that this vulnerability can also lead to severe consequences that hurt user privacy, including the leakage of sensitive information like precise locations, daily activities, and demographics. Ultimately, we discuss the potential countermeasures that may be used to mitigate this vulnerability and location spoofing attack.

Title: How to Hide MetaData in MLS-Like Secure Group Messaging: Simple, Modular, and Post-Quantum Abstract: ABSTRACTSecure group messaging (SGM) protocols allow large groups of users to communicate in a secure and asynchronous manner. In recent years, continuous group key agreements (CGKAs) have provided a powerful abstraction to reason on the security properties we expect from SGM protocols. While robust techniques have been developed to protect the contents of conversations in this context, it is in general more challenging to protect metadata (e.g. the identity and social relationships of group members), since their knowledge is often needed by the server in order to ensure the proper function of the SGM protocol. In this work, we provide a simple and generic wrapper protocol that upgrades non-metadata-hiding CGKAs into metadata-hiding CGKAs. Our key insight is to leverage the existence of a unique continuously evolving group secret key shared among the group members. We use this key to perform a group membership authentication protocol that convinces the server in an anonymous manner that a user is a legitimate group member. Our technique only uses a standard signature scheme, and thus, the wrapper protocol can be instantiated from a wide range of assumptions, including post-quantum ones. It is also very efficient, as it increases the bandwidth cost of the underlying CGKA operations by at most a factor of two. To formally prove the security of our protocol, we use the universal composability (UC) framework and model a new ideal functionality ℱmhCGKA capturing the correctness and security guarantee of metadata-hiding CGKA. To capture the above intuition of a "wrapper'' protocol, we also define a restricted ideal functionality ℱctxt CGKA, which roughly captures a non-metadata-hiding CGKA. We then show that our wrapper protocol UC-realizes ℱmhCGKA in the ℱctxtCGKA -hybrid model, which in particular formalizes the intuition that any non-metadata-hiding CGKA can be modularly bootstrapped into metadata-hiding CGKA.

Title: Behind the Scenes of RPKI Abstract: ABSTRACTBest practices for making RPKI resilient to failures and attacks recommend using multiple URLs and certificates for publication points as well as multiple relying parties. We find that these recommendations are already supported by 63% of the ASes with RPKI. In this work we explore the dependency of the RPKI deployments on their DNS components. We find that the resilience of RPKI can be subverted through DNS. We identify two key factors. First, we find that 42.8% of the ASes with multiple relying parties use a single resolver for looking up the RPKI publication points and the DNS resolvers of 82.9% of the relying parties are all located on a single AS. Both introduce a single point of failure. Second, we also find problems with DNSSEC deployments: more than 24% of the resolvers in RPKI experience failures with signed DNS responses and as a result cannot locate the RPKI publication points and cannot validate RPKI, and 60% of the resolvers that support DNSSEC do not validate records signed with new algorithms, accepting responses also with invalid signatures. We experimentally find that adversaries can disable RPKI in 56.7% of the ASes that have vulnerable DNS components. Our simulations show that disabling RPKI exposes ASes to prefix hijack attacks. Our work demonstrates, that resilience of systems, like RPKI, cannot be achieved in isolation due to complex inter-dependencies with other systems.

Title: Kryvos: Publicly Tally-Hiding Verifiable E-Voting Abstract: ABSTRACTElections are an important corner stone of democratic processes. In addition to publishing the final result (e.g., the overall winner), elections typically publish the full tally consisting of all (aggregated) individual votes. This causes several issues, including loss of privacy for both voters and election candidates as well as so-called Italian attacks that allow for easily coercing voters. Several e-voting systems have been proposed to address these issues by hiding (parts of) the tally. This property is called tally-hiding. Existing tally-hiding e-voting systems in the literature aim at hiding (part of) the tally from everyone, including voting authorities, while at the same time offering verifiability, an important and standard feature of modern e-voting systems which allows voters and external observers to check that the published election result indeed corresponds to how voters actually voted. In contrast, real elections often follow a different common practice for hiding the tally: the voting authorities internally compute (and learn) the full tally but publish only the final result (e.g., the winner). This practice, which we coin publicly tally-hiding, indeed solves the aforementioned issues for the public, but currently has to sacrifice verifiability due to a lack of practical systems. In this paper, we close this gap. We formalize the common notion of publicly tally-hiding and propose the first provably secure verifiable e-voting system, called Kryvos, which directly targets publicly tally-hiding elections. We instantiate our system for a wide range of both simple and complex voting methods and various result functions. We provide an extensive evaluation which shows that Kryvos is practical and able to handle a large number of candidates, complex voting methods and result functions. Altogether, Kryvos shows that the concept of publicly tally-hiding offers a new trade-off between privacy and efficiency that is different from all previous tally-hiding systems and which allows for a radically new protocol design resulting in a practical e-voting system.

Title: SpecDoctor: Differential Fuzz Testing to Find Transient Execution Vulnerabilities Abstract: ABSTRACTTransient execution vulnerabilities have critical security impacts to software systems since those break the fundamental security assumptions guaranteed by the CPU. Detecting these critical vulnerabilities in the RTL development stage is particularly important, as it offers a chance to fix the vulnerability early before reaching the chip manufacturing stage. This paper proposes SpecDoctor, an automated RTL fuzzer to discover transient execution vulnerabilities in the CPU. To be specific, SpecDoctor designs a fuzzing template, allowing it to test all different scenarios of transient execution vulnerabilities (e.g., Meltdown, Spectre, ForeShadow, etc.) with a single template. Then SpecDoctor performs a multi-phased fuzzing, where each phase is dedicated to solve an individual vulnerability constraint in the RTL context, thereby effectively finding the vulnerabilities. We implemented and evaluated SpecDoctor on two out-of-order RISC-V CPUs, Boom and NutShell-Argo. During the evaluation, SpecDoctor found transient-execution vulnerabilities which share the similar attack vectors as the previous works. Furthermore, SpecDoctor found two interesting variants which abuse unique attack vectors: Boombard, and Birgus. Boombard exploits an unknown implementation bug in RISC-V Boom, exacerbating it into a critical transient execution vulnerability. Birgus launches a Spectre-type attack with a port contention side channel in NutShell CPU, which is constructed using a unique combination of instructions. We reported the vulnerabilities, and both are confirmed by the developers, illustrating the strong practical impact of SpecDoctor.

Title: Differentially Private Triangle and 4-Cycle Counting in the Shuffle Model Abstract: ABSTRACTSubgraph counting is fundamental for analyzing connection patterns or clustering tendencies in graph data. Recent studies have applied LDP (Local Differential Privacy) to subgraph counting to protect user privacy even against a data collector in social networks. However, existing local algorithms suffer from extremely large estimation errors or assume multi-round interaction between users and the data collector, which requires a lot of user effort and synchronization. In this paper, we focus on a one-round of interaction and propose accurate subgraph counting algorithms by introducing a recently studied shuffle model. We first propose a basic technique called wedge shuffling to send wedge information, the main component of several subgraphs, with small noise. Then we apply our wedge shuffling to counting triangles and 4-cycles -- basic subgraphs for analyzing clustering tendencies -- with several additional techniques. We also show upper bounds on the estimation error for each algorithm. We show through comprehensive experiments that our one-round shuffle algorithms significantly outperform the one-round local algorithms in terms of accuracy and achieve small estimation errors with a reasonable privacy budget, e.g., smaller than 1 in edge DP.

Title: On the Success Rate of Side-Channel Attacks on Masked Implementations: Information-Theoretical Bounds and Their Practical Usage Abstract: ABSTRACTThis study derives information-theoretical bounds of the success rate (SR) of side-channel attacks on masked implementations. We first develop a communication channel model representing side-channel attacks on masked implementations. We then derive two SR bounds based on the conditional probability distribution and mutual information of shares. The basic idea is to evaluate the upper-bound of the mutual information between the non-masked secret value and the side-channel trace by the conditional probability distribution of shares given its leakage, with a help of the Walsh-Hadamard transform. With the derived theorems, we also prove the security of masking schemes: the SR decreases exponentially with an increase in the number of masking shares, under a much more relaxed condition than the previous proof. To validate and utilize our theorems in practice, we propose a deep-learning-based profiling method for approximating the conditional probability distribution of shares to estimate the SR bound and the number of traces required for attacking a given device. We experimentally confirm that our bounds are much stronger than the conventional bounds on masked implementations, which validates the relevance of our theorems to practice.

Title: AI/ML for Network Security: The Emperor has no Clothes Abstract: ABSTRACTSeveral recent research efforts have proposed Machine Learning (ML)-based solutions that can detect complex patterns in network traffic for a wide range of network security problems. However, without understanding how these black-box models are making their decisions, network operators are reluctant to trust and deploy them in their production settings. One key reason for this reluctance is that these models are prone to the problem of underspecification, defined here as the failure to specify a model in adequate detail. Not unique to the network security domain, this problem manifests itself in ML models that exhibit unexpectedly poor behavior when deployed in real-world settings and has prompted growing interest in developing interpretable ML solutions (e.g., decision trees) for "explaining'' to humans how a given black-box model makes its decisions. However, synthesizing such explainable models that capture a given black-box model's decisions with high fidelity while also being practical (i.e., small enough in size for humans to comprehend) is challenging. In this paper, we focus on synthesizing high-fidelity and low-complexity decision trees to help network operators determine if their ML models suffer from the problem of underspecification. To this end, we present Trustee, a framework that takes an existing ML model and training dataset as input and generates a high-fidelity, easy-to-interpret decision tree and associated trust report as output. Using published ML models that are fully reproducible, we show how practitioners can use Trustee to identify three common instances of model underspecification; i.e., evidence of shortcut learning, presence of spurious correlations, and vulnerability to out-of-distribution samples.

Title: DISTINCT: Identity Theft using In-Browser Communications in Dual-Window Single Sign-On Abstract: ABSTRACTSingle Sign-On (SSO) protocols like OAuth 2.0 and OpenID Connect 1.0 are cornerstones of modern web security, and have received much academic attention. Users sign in at a trusted Identity Provider (IdP) that subsequently allows many Service Providers (SPs) to verify the users' identities. Previous research concentrated on the standardized - called textbook SSO in this paper - authentication flows, which rely on HTTP redirects to transfer identity tokens between the SP and IdP. However, modern web applications like single page apps may not be able to execute the textbook flow because they lose the local state in case of HTTP redirects. By using novel browser technologies, such as postMessage, developers designed and implemented SSO protocols that were neither documented nor analyzed thoroughly. We call them dual-window SSO flows. In this paper, we provide the first comprehensive evaluation of dual-window SSO flows. In particular, we focus on the In-Browser Communication (InBC) used to exchange authentication tokens between SPs and IdPs in iframes and popups. We automate our analysis by developing Distinct - a tool that dynamically analyzes the JavaScript code executing as part of the SSO flow. Distinct translates the flow into a sequence diagram depicting all communicating entities and their exchanged messages, highlights insecure communication channels, and quantifies novel threats in dual-window SSO flows. We found that 56% of the SPs in the Tranco top 1k list support dual-window SSO. Surprisingly, 28% of the SPs implemented dual-window SSO without using official SDKs, leading to identity theft and XSS in 31% of these self-implemented SPs.

Title: Evocatio: Conjuring Bug Capabilities from a Single PoC Abstract: ABSTRACTThe popularity of coverage-guided greybox fuzzers has led to a tsunami of security-critical bugs that developers must prioritize and fix. Knowing the capabilities a bug exposes (e.g., type of vulnerability, number of bytes read/written) enables prioritization of bug fixes. Unfortunately, understanding a bug's capabilities is a time consuming process, requiring (a) an understanding of the bug's root cause, (b) an understanding how an attacker may exploit the bug, and (c) the development of a patch mitigating these threats. This is a mostly-manual process that is qualitative and arbitrary, potentially leading to a misunderstanding of the bug's capabilities. Evocatio automatically discovers a bug's capabilities. Evocatio analyzes a crashing test case (i.e., an input exposing a bug) to understand the full extent of how an attacker can exploit a bug. Evocatio leverages a capability-guided fuzzer to efficiently uncover new bug capabilities (rather than only generating a single crashing test case for a given bug, as a traditional greybox fuzzer does). We evaluate Evocatio on 38 bugs (34 CVEs and four bug reports) across eight open-source applications. From these bugs, Evocatio: (i) discovered 10× more capabilities (that is, the number of unique capabilities induced by a set of crashes was 10× higher) than AFL++'s crash exploration mode; (ii) converted 19 of the 38 bugs to new bug types (demonstrating the limitations of manual qualitative analysis); and (iii) generated new proof-of-concept (PoC) test cases violating patches for 7 out of 16 tested CVEs, one of which still triggers in the latest version of the software.

Title: Understanding IoT Security from a Market-Scale Perspective Abstract: ABSTRACTConsumer IoT products and services are ubiquitous; yet, a proper characterization of consumer IoT security is infeasible without an understanding of what IoT products are on the market, i.e., without a market-scale perspective. This paper seeks to close this gap by developing the IoTSpotter framework, which automatically constructs a market-scale snapshot of mobile-IoT apps, i.e., mobile apps that are used as companions or automation providers to IoT devices. IoTSpotter also extracts artifacts that allow us to examine the security of this snapshot in the IoT context (e.g., devices supported by apps, IoT-specific libraries). Using IoTSpotter, we identify 37,783 mobile-IoT apps from Google Play, the largest set of mobile-IoT apps so far, and uncover 7 key results in the process (ℛ1-ℛ7). We leverage this dataset to perform three key security analyses that lead to 10 impactful security findings (F1-F10) that demonstrate the current state of mobile-IoT apps. Our analysis uncovers severe cryptographic violations in 94.11% (863/917) mobile-IoT apps with >1 million installs each, 65 vulnerable IoT-specific libraries affected by 79 unique CVEs, and used by 40 popular apps, and 7,887 apps that is affected by the Janus vulnerability. Finally, a case study with 18 popular mobile-IoT apps uncovers the critical impact of the vulnerabilities in them on important IoT artifacts and functions, motivating the development of mobile security analysis contextualized to IoT.

Title: SymLM: Predicting Function Names in Stripped Binaries via Context-Sensitive Execution-Aware Code Embeddings Abstract: ABSTRACTPredicting function names in stripped binaries is an extremely useful but challenging task, as it requires summarizing the execution behavior and semantics of the function in human languages. Recently, there has been significant progress in this direction with machine learning. However, existing approaches fail to model the exhaustive function behavior and thus suffer from the poor generalizability to unseen binaries. To advance the state of the art, we present a function Symbol name prediction and binary Language Modeling (SymLM) framework, with a novel neural architecture that learns the comprehensive function semantics by jointly modeling the execution behavior of the calling context and instructions via a novel fusing encoder. We have evaluated SymLM with 1,431,169 binary functions from 27 popular open source projects, compiled with 4 optimizations (O0-O3) for 4 different architectures (i.e., x64, x86, ARM, and MIPS) and 4 obfuscations. SymLM outperforms the state-of-the-art function name prediction tools by up to 15.4%, 59.6%, and 35.0% in precision, recall, and F1 score, with significantly better generalizability and obfuscation resistance. Ablation studies also show that our design choices (e.g., fusing components of the calling context and execution behavior) substantially boost the performance of function name prediction. Finally, our case studies further demonstrate the practical use cases of SymLM in analyzing firmware images.

Title: P-Verifier: Understanding and Mitigating Security Risks in Cloud-based IoT Access Policies Abstract: ABSTRACTModern IoT device manufacturers are taking advantage of the managed Platform-as-a-Service (PaaS) and Infrastructure-as-a-Service (IaaS) IoT clouds (e.g., AWS IoT, Azure IoT) for secure and convenient IoT development/deployment. The IoT access control is achieved by manufacturer-specified, cloud-enforced IoT access policies (cloud-standard JSON documents, called IoT Policies) stating which users can access which IoT devices/resources under what constraints. In this paper, we performed a systematic study on the security of cloud-based IoT access policies on modern PaaS/IaaS IoT clouds. Our research shows that the complexity in the IoT semantics and enforcement logic of the policies leaves tremendous space for device manufacturers to program a flawed IoT access policy, introducing convoluted logic flaws which are non-trivial to reason about. In addition to challenges/mistakes in the design space, it is astonishing to find that mainstream device manufacturers also generally make critical mistakes in deploying IoT Policies thanks to the flexibility offered by PaaS/IaaS clouds and the lack of standard practices for doing so. Our assessment of 36 device manufacturers and 310 open-source IoT projects highlights the pervasiveness and seriousness of the problems, which once exploited, can have serious impacts on IoT users' security, safety, and privacy. To help manufacturers identify and easily fix IoT Policy flaws, we introduce P-Verifier, a formal verification tool that can automatically verify cloud-based IoT Policies. With evaluated high effectiveness and low performance overhead, P-Verifier will contribute to elevating security assurance in modern IoT deployments and access control. We responsibly reported all findings to affected vendors and fixes were deployed or on the way.

Title: A Scalable and Dynamic ACL System for In-Network Defense Abstract: ABSTRACTIn-network/in-switch Access Control List (ACL) is an essential security component of modern networks. In high-speed networks, ACL rules are often placed in a switch's Ternary Content-Addressable Memory (TCAM) for timely ACL match-action and management (e.g. insertion and deletion). However, TCAM-based ACL systems are encountering an scalability issue owing to increasing demand on AI-powered autonomous defenses that detect and block attacks online, which inevitably derives finer-grained ACL rules. Existing solutions minimize the TCAM usage by partially offloading ACL matching into larger Static Random-Access Memory (SRAM) or customized hardware. Nevertheless, current SRAM-based solutions induce high management costs, especially a high rule-deployment latency, which delays time-sensitive defense actions. Also, the customized hardware approaches have its own scalability issue. To support autonomous defenses at a scale, in this paper, we propose an in-switch ACL system called PortCatcher, which breaks the trade-off between scalability and rule management latency. System-wise, we detach layer-4 port matching from TCAM for improving its memory efficiency. Algorithm-wise, we introduce a novel port (range) rule representation concept, called linear range map (LRM), which enables port (range) matching in SRAM-based hash tables. LRM guarantees not only fast and scalable port matching but also low-latency ACL management for timely defenses. With real-world ACL datasets, we show that PortCatcher saves 74%-90% TCAM space compared to state-of-the-art approaches by adding small overhead to SRAM (0.49 SRAM entry per ACL rule). Also, we deploy PortCatcher on a programmable switch to demonstrate that PortCatcher can serve 5-tuple rule matching at a line rate, where port rules are completely matched in SRAM. With a use case study, namely autonomous attack mitigation, we show that PortCatcher has a negligible rule management latency to block attack flows (i.e. 94.42% of rules deployed within 10 ms).

Title: TRACER: Signature-based Static Analysis for Detecting Recurring Vulnerabilities Abstract: ABSTRACTSimilar software vulnerabilities recur because developers reuse existing vulnerable code, or make similar mistakes when implementing the same logic. Recently, various analysis techniques have been proposed to find syntactically recurring vulnerabilities via code reuse. However, limited attention has been devoted to semantically recurring ones that share the same vulnerable behavior in different code structures. In this paper, we present a general analysis framework, called TRACER, for detecting such recurring vulnerabilities. TRACER is based on a taint analysis that can detect various types of vulnerabilities. For a given set of known vulnerabilities, the taint analysis extracts vulnerable traces and establishes a signature database of them. When a new unseen program is analyzed, TRACER compares all potentially vulnerable traces reported by the analysis with the known vulnerability signatures. Then, TRACER reports a list of potential vulnerabilities ranked by the similarity score. We evaluate TRACER on 273 Debian packages in C/C++. Our experiment results demonstrate that TRACER is able to find 281 previously unknown vulnerabilities with 6 CVE identifiers assigned.

Title: HyperDbg: Reinventing Hardware-Assisted Debugging Abstract: ABSTRACTSoftware analysis, debugging, and reverse engineering have a crucial impact in today's software industry. Efficient and stealthy debuggers are especially relevant for malware analysis. However, existing debugging platforms fail to address a transparent, effective, and high-performance low-level debugger due to their detectable fingerprints, complexity, and implementation restrictions. In this paper,\footnote[2]For the extended version of this paper which includes additional appendices, refer to: https://arxiv.org/abs/2207.05676 . we present a new hypervisor-assisted debugger for high-performance and stealthy debugging of user and kernel applications. To accomplish this, HyperDbg relies on state-of-the-art hardware features available in today's CPUs, such as VT-x and Extended Page Table (EPT). In contrast to other widely used existing debuggers, we design HyperDbg using a custom hypervisor, making it independent of OS functionality or API. We propose hardware-based instruction-level emulation and OS-level API hooking via extended page tables to increase the stealthiness. Our results of the dynamic analysis of 10,853 malware samples show that HyperDbg 's stealthiness allows debugging on average 22% and 26% more samples thanWinDbg andx64dbg, respectively. Moreover, in contrast to existing debuggers, HyperDbg is not detected by any of the 13 tested packers and protectors. We improve the performance over other debuggers by deploying a VMX-compatible script engine, eliminating unnecessary context switches. Our experiment on three concrete debugging scenarios shows that compared toWinDbg as the only kernel debugger, HyperDbg performs step-in, conditional breaks, and syscall recording, 2.98x, 1319x, and 2018x faster, respectively. We finally show real-world applications, such as a 0-day analysis, structure reconstruction for reverse engineering, software performance analysis, and code-coverage analysis.

Title: RedShift: Transparent SNARKs from List Polynomial Commitments Abstract: ABSTRACTWe introduce an efficient transformation from univariate polynomial commitment based zk-SNARKs to their transparent counterparts. The transformation is achieved with the help of a new IOP primitive which we call a list polynomial commitment. This primitive is applicable for preprocessing zk-SNARKs over both prime and binary fields. We present the primitive itself along with a soundness analysis of the transformation and instantiate it with an existing universal proof system. We also present benchmarks for a proof of concept implementation alongside a comparison with the current non-transparent state-of-the-art. Our results show competitive efficiency both in terms of proof size and generation times. At the 80-bit security level, our benchmarks provide proof generation times of about a minute and proof sizes of around 515 KB for a circuit with one million gates.

Title: NTRU-v-um: Secure Fully Homomorphic Encryption from NTRU with Small Modulus Abstract: ABSTRACTNTRUEncrypt is one of the first lattice-based encryption schemes. Furthermore, the earliest fully homomorphic encryption (FHE) schemes rely on the NTRU problem. Currently, NTRU is one of the leading candidates in the NIST post-quantum standardization competition. What makes NTRU appealing is the age of the cryptosystem and relatively good performance. Unfortunately, FHE based on NTRU became impractical due to efficient attacks on NTRU instantiations with "overstretched'' modulus. In particular, currently, NTRU-based FHE schemes to support a reasonable circuit depth require instantiating NTRU with a very large modulus. Breaking the NTRU problem for such large moduli turns out to be easy. Due to these attacks, any serious work on practical NTRU-based FHE essentially stopped. In this paper, we reactivate research on practical FHE that can be based on NTRU. We design an efficient bootstrapping scheme in which the noise growth is small enough to keep the modulus to dimension ratio relatively small, thus avoiding the negative consequences of "overstretching'' the modulus. Our bootstrapping algorithm is an accumulator-type bootstrapping scheme analogous to AP/FHEW/TFHE. Finally, we show that we can use the bootstrapping procedure to compute any function over \mathbbZ _t. Consequently, we obtain one of the fastest FHE bootstrapping schemes able to compute any function over elements of a finite field alongside reducing the error.

Title: Low-Latency Hardware Private Circuits Abstract: ABSTRACTOver the last years, the rise of the IoT, and the connection of mobile - and hence physically accessible - devices, immensely enhanced the demand for fast and secure hardware implementations of cryptographic algorithms which offer thorough protection against SCA attacks. Among a variety of proposed countermeasures against SCA, masking has transpired to be a promising candidate, attracting significant attention in both, academia and industry. Here, abstract adversary models have been derived, aiming to accurately model real-world attack scenarios, while being sufficiently simple to enable formally proving the SCA resilience of masked implementations on an algorithmic level. In the context of hardware implementations, the robust probing model has become highly relevant for proving SCA resilience due to its capability to model physical defaults like glitches and data transitions. As constructing a correct and secure masked variant of large and complex circuits is a challenging task, a new line of research has recently emerged, aiming to design small, masked subcircuits - realizing for instance a simple AND gate - which still guarantee security when composed to a larger circuit. Although several designs realizing such composable subcircuits - commonly referred to as gadgets - have been proposed, negligible research was conducted in order to find trade-offs between different overhead metrics, like randomness requirement, latency, and area consumption. In this work, we present HPC3, a hardware gadget which is trivially composable under the notion of PINI in the glitch-extended robust probing model. HPC3 realizes a two-input AND gate in one clock cycle which is generalized for any arbitrary security order. Existing state-of-the-art PINI-gadgets either require a latency of two clock cycles or are limited to first-order security. In short, HPC3 enables the designer to trade double the randomness for half the latency compared to existing gadgets, providing high flexibility and enabling the designer to gain significantly more speed in real-time applications.

Title: Leakage Inversion: Towards Quantifying Privacy in Searchable Encryption Abstract: ABSTRACTSearchable encryption (SE) provides cryptographic guarantees that a user can efficiently search over encrypted data while only disclosing patterns about the data, also known as leakage. Recently, the community has developed leakage-abuse attacks that shed light on what an attacker can infer about the underlying sensitive information using the aforementioned leakage. A glaring missing piece in this effort is the absence of a systematic and rigorous method that quantifies the privacy guarantees of SE. In this work, we put forth the notion of leakage inversion that quantifies privacy in SE. Our insight is that the leakage is a function and, thus, one can define its inverse which corresponds to the collection of databases that reveal structurally equivalent patterns to the original plaintext database. We call this collection of databases the reconstruction space and we rigorously study its properties that impact the privacy of an SE scheme such as the entropy of the reconstruction space and the distance of its members from the original plaintext database. Leakage inversion allows for a foundational algorithmic analysis of the privacy offered by SE and we demonstrate this by defining closed-form expressions and lower/upper bounds on the properties of the reconstruction space for both keyword-based and range-based databases. We use leakage inversion in three scenarios: (i) we quantify the impact that auxiliary information, a typical cryptanalytic assumption, has to the overall privacy, (ii) we quantify how privacy is affected in case of restricting range schemes to respond to a limited number of queries, and (iii) we study the efficiency vs. privacy trade-off offered by proposed padding defenses. We use real-world databases in all three scenarios and we draw theoretically-grounded new insights about the interplay between leakage, attacks, defenses, and efficiency.

Title: PentaGOD: Stepping beyond Traditional GOD with Five Parties Abstract: ABSTRACTSecure multiparty computation (MPC) is increasingly being used to address privacy issues in various applications. The recent work of Alon et al. (CRYPTO'20) identified the shortcomings of traditional MPC and defined a Friends-and-Foes (FaF) security notion to address the same. We showcase the need for FaF security in real-world applications such as dark pools. This subsequently necessitates designing concretely efficient FaF-secure protocols. Towards this, keeping efficiency at the center stage, we design ring-based FaF-secure MPC protocols in the small-party honest-majority setting. Specifically, we provide (1,1)-FaF secure 5 party computation protocols (5PC) that consider one malicious and one semi-honest corruption and constitutes the optimal setting for attaining honest-majority. At the heart of it lies the multiplication protocol that requires a single round of communication with 8 ring elements (amortized). To facilitate having FaF-secure variants for several applications, we design a variety of building blocks optimized for our FaF setting. The practicality of the designed (1,1)-FaF secure 5PC framework is showcased by benchmarking dark pools. In the process, we also improve the efficiency and security of the dark pool protocols over the existing traditionally secure ones. This improvement is witnessed as a gain of up to 62x in throughput compared to the existing ones. Finally, to demonstrate the versatility of our framework, we also benchmark popular deep neural networks.

Title: Hammurabi: A Framework for Pluggable, Logic-Based X.509 Certificate Validation Policies Abstract: ABSTRACTThis paper proposes using a logic programming language to disentangle X.509 certificate validation policy from mechanism. Expressing validation policies in a logic programming language provides multiple benefits. First, policy and mechanism can be more independently written, augmented, and analyzed compared to the current practice of interweaving them within a C or C++ implementation. Once written, these policies can be easily shared and modified for use in different TLS clients. Further, logic programming allows us to determine when clients differ in their policies and use the power of imputation to automatically generate interesting certificates, e.g., a certificate that will be accepted by one browser but not by another. We present a new framework called Hammurabi for expressing validation policies, and we demonstrate that we can express the complex policies of the Google Chrome and Mozilla Firefox web browsers in this framework. We confirm the fidelity of the Hammurabi policies by comparing the validation decisions they make with those made by the browsers themselves on over ten million certificate chains derived from Certificate Transparency logs, as well as 100K synthetic chains. We also use imputation to discover nine validation differences between the two browsers' policies. Finally, we demonstrate the feasibility of integrating Hammurabi into Firefox and the Go language in less than 100 lines of code each.

Title: Collect Responsibly But Deliver Arbitrarily?: A Study on Cross-User Privacy Leakage in Mobile Apps Abstract: ABSTRACTRecent years have witnessed the interesting trend that modern mobile apps perform more and more likely as user-to-user platforms, where app users can be freely and conveniently connected. Upon these platforms, rich and diverse data is often delivered across users, which brings users great conveniences and plentiful services, but also introduces privacy security concerns. While prior work has primarily studied illegitimate personal data collection problems in mobile apps, few paid little attention to the security of this emerging user-to-user platform feature, thus providing a rather limited understanding of the privacy risks in this aspect. In this paper, we focus on the security of the user-to-user platform feature and shed light on its caused insufficiently-studied but critical privacy risk, which is brought forward by cross-user personal data over-delivery (denoted as XPO). For the first time, this paper reveals the landscape of such XPO risk in wild, along with prevalence and severity assessment. To achieve this, we design a novel automated risk detection framework, named XPOChecker, that leverages the advantages of machine learning and program analysis to extensively and precisely identify potential privacy risks during user-to-user connections, and regulate whether the delivered data is legitimate or not. By applying XPOChecker on 13,820 real-world popular Android apps, we find that XPO is prevalent in practice, with 1,902 apps (13.76%) being affected. In addition to the mere exposure of diverse private user data which causes serious and broad privacy infringement, we demonstrate that the XPO exploits can invalidate privacy preservation mechanisms, leak business secrets, and even restore the sensitive membership of victims which potentially poses personal safety threats. Furthermore, we also confirm the existence of XPO risks in iOS apps for the first time. Last, to help understand and prevent XPO, we have responsibly launched two notification campaigns to inform the developers of the affected apps, with the conclusion of five underlying lessons from developers' feedback. We hope our work can make up for the deficiency of the understandings of XPO, help developers avoid XPO, and motivate further researches.

Title: PACMem: Enforcing Spatial and Temporal Memory Safety via ARM Pointer Authentication Abstract: ABSTRACTMemory safety is a key security property that stops memory corruption vulnerabilities. Different types of memory safety enforcement solutions have been proposed and adopted by sanitizers or mitigations to catch and stop such bugs, at the development or deployment phase. However, existing solutions either provide partial memory safety or have overwhelmingly high performance overheads. In this paper, we present a novel sanitizer PACMem to efficiently catch spatial and temporal memory safety bugs. PACMem removes the majority of the overheads by sealing metadata in pointers through the COTS hardware feature -- ARM PA (Pointer Authentication) and saving the overhead of pointer metadata tracking. We have developed a prototype of PACMem and systematically evaluated its security and performance on the Magma, Juliet, Nginx, and SPEC CPU2017 test suites. In our evaluation, PACMem shows no false positives together with negligible false negatives, while introducing stronger bug detection capabilities and lower performance overheads than state-of-the-art sanitizers, including HWASan, ASan, SoftBound+CETS, Memcheck, LowFat, and PTAuth. Compared to the widely deployed ASan, PACMem has no false positives and much fewer false negatives and reduces the runtime overheads by 15.80% and the memory overheads by 71.58%.

Title: Overo: Sharing Private Audio Recordings Abstract: ABSTRACTThe use of smartphones as voice recorders has made it easy to record audios as proof of conversations, but sharing of such audio evidence incurs speech and voice privacy risks. However, protecting speech/voice privacy without losing audio authenticity is challenging. The conventional post-process redaction and voice conversion of audio recordings, which invalidate their original signatures, make the audio unverifiable and prone to tampering. In this paper, we present Overo, an audio recording/sharing solution that supports privacy processing without losing audio authenticity. Overo records a realtime audio stream in the standard AAC-encoded format and allows privacy post-processing prior to sharing of audios while keeping their original signatures valid (even after the post redaction and voice conversion), guaranteeing no tampering since the time of their recording. Therefore, users can post-process their recordings to desired levels of privacy on speech (what content to redact) and speakers (whose voice to disguise) at the time of audio release, and still prove their authenticity. Overo is readily implementable in today's commodity smartphones. Our prototype on iPhones/Android phones demonstrates the production of AAC-compliant, tamperproof, and self-authenticating audios with speech/voice privacy protected based on users' post-recording decisions.

Title: Ready Raider One: Exploring the Misuse of Cloud Gaming Services Abstract: ABSTRACTCloud gaming has become an emerging computing paradigm in recent years, allowing computer games to offload complex graphics and logic computation to the cloud. To deliver a smooth and high-quality gaming experience, cloud gaming services have invested abundant computing resources in the cloud, including adequate CPUs, top-tier GPUs, and high-bandwidth Internet connections. Unfortunately, the abundant computing resources offered by cloud gaming are vulnerable to misuse and exploitation for malicious purposes. In this paper, we present an in-depth study on security vulnerabilities in cloud gaming services. Specifically, we reveal that adversaries can purposely inject malicious programs/URLs into the cloud gaming services via game mods. Using the provided features such as in-game subroutines, game launch options, and built-in browsers, adversaries are able to execute the injected malicious programs/URLs in cloud gaming services. To demonstrate that such vulnerabilities pose a serious threat, we conduct four proof-of-concept attacks on cloud gaming services. Two of them are to abuse the CPUs and GPUs in cloud gaming services to mine cryptocurrencies with attractive profits and train machine learning models at a trivial cost. The other two are to exploit the high-bandwidth connections provided by cloud gaming for malicious Command & Control and censorship circumvention. Finally, we present several countermeasures for cloud gaming services to protect their valuable assets from malicious exploitation.

Title: When Evil Calls: Targeted Adversarial Voice over IP Network Abstract: ABSTRACTAs the COVID-19 pandemic fundamentally reshaped the remote life and working styles, Voice over IP (VoIP) telephony and video conferencing have become a primary method of connecting communities together. However, little has been done to understand the feasibility and limitations of delivering adversarial voice samples via such communication channels. In this paper, we propose TAINT - Targeted Adversarial Voice over IP Network, the first targeted, query-efficient, hard label black-box, adversarial attack on commercial speech recognition platforms over VoIP. The unique channel characteristics of VoIP pose significant new challenges, such as signal degradation, random channel noise, frequency selectivity, etc. To address these challenges, we systematically analyze the structure and channel characteristics of VoIP through reverse engineering. A noise-resilient efficient gradient estimation method is then developed to ensure a steady and fast convergence of the adversarial sample generation process. We demonstrate our attack in both over-the-air and over-the-line settings on four commercial automatic speech recognition (ASR) systems over the five most popular VoIP Conferencing Software (VCS). We show that TAINT can achieve performance that is comparable to the existing methods even with the addition of VoIP channel. Even in the most challenging scenario where there is an active speaker in Zoom, TAINT can still succeed within 10 attempts while staying out of the speaker focus of the video conference.

Title: Matproofs: Maintainable Matrix Commitment with Efficient Aggregation Abstract: ABSTRACTWe present Matproofs, a matrix commitment scheme that allows one to commit to any matrix and then open any subset of the matrix entries. If we encode any vector as a matrix, by committing to the matrix Matproofs may function well as a vector commitment (VC) scheme. We show that Matproofs are simultaneously concise, aggregatable, easily updatable and maintainable. With these promising features, Matproofs give solutions to payment-only stateless cryptocurrencies with lower bandwidth and computational complexity. Compared with Hyperproofs, the only existing VC scheme that is simultaneously aggregatable, easily updatable and maintainable, Matproofs achieve the additional property of conciseness. Furthermore, in the worst case, the proof aggregation and verification in Matproofs are 700x and 10x faster than Hyperproofs, respectively.

Title: Acquirer: A Hybrid Approach to Detecting Algorithmic Complexity Vulnerabilities Abstract: ABSTRACTAlgorithmic Complexity (AC) Denial-of-Service attacks have been a threat for over twenty years. Attackers craft particular input vectors to trigger the worst-case logic of some code running on the server side, which leads to high resource consumption and performance degradation. In response, several vulnerability detection tools have been developed to help developers prevent such attacks. Nevertheless, these state-of-the-art tools either focus on a specific type of vulnerability or suffer from state explosion. They are either limited to a small detection scope or unable to run efficiently. This paper aims to develop a fully automated approach to effectively and efficiently detecting AC vulnerabilities. We present the design and implementation of Acquirer, which detects AC vulnerabilities in Java programs. Acquirer first statically locates potentially vulnerable structures in the target program, then performs efficient selective path exploration to dynamically verify the existence of two different execution paths with a significant computation cost difference. The vulnerable structures it detects can also help the developers analyze and fix the corresponding vulnerabilities. We evaluated Acquirer with two widely used benchmark datasets and compared it with four state-of-the-art tools. In the evaluation, it detected 22 known AC vulnerabilities, which substantially out performed all the existing tools together. Besides, it discovered 11 previously unknown AC vulnerabilities in popular real-world applications. Our evaluation demonstrates that Acquirer is highly effective and efficient in automatically detecting AC vulnerabilities.

Title: StolenEncoder: Stealing Pre-trained Encoders in Self-supervised Learning Abstract: ABSTRACTPre-trained encoders are general-purpose feature extractors that can be used for many downstream tasks. Recent progress in self-supervised learning can pre-train highly effective encoders using a large volume of unlabeled data, leading to the emerging encoder as a service (EaaS). A pre-trained encoder may be deemed confidential because its training often requires lots of data and computation resources as well as its public release may facilitate misuse of AI, e.g., for deepfakes generation. In this paper, we propose the first attack called StolenEncoder to steal pre-trained image encoders. We evaluate StolenEncoder on multiple target encoders pre-trained by ourselves and three real-world target encoders including the ImageNet encoder pre-trained by Google, CLIP encoder pre-trained by OpenAI, and Clarifai's General Embedding encoder deployed as a paid EaaS. Our results show that the encoders stolen by StolenEncoder have similar functionality with the target encoders. In particular, the downstream classifiers built upon a target encoder and a stolen encoder have similar accuracy. Moreover, stealing a target encoder using StolenEncoder requires much less data and computation resources than pre-training it from scratch. We also explore three defenses that perturb feature vectors produced by a target encoder. Our evaluation shows that these defenses are not enough to mitigate StolenEncoder.

Title: LoneNeuron: A Highly-Effective Feature-Domain Neural Trojan Using Invisible and Polymorphic Watermarks Abstract: ABSTRACTThe wide adoption of deep neural networks (DNNs) in real-world applications raises increasing security concerns. Neural Trojans embedded in pre-trained neural networks are a harmful attack against the DNN model supply chain. They generate false outputs when certain stealthy triggers appear in the inputs. While data-poisoning attacks have been well studied in the literature, code-poisoning and model-poisoning backdoors only start to attract attention until recently. We present a novel model-poisoning neural Trojan, namely LoneNeuron, which responds to feature-domain patterns that transform into invisible, sample-specific, and polymorphic pixel-domain watermarks. With high attack specificity, LoneNeuron achieves a 100% attack success rate, while not affecting the main task performance. With LoneNeuron's unique watermark polymorphism property, the same feature-domain trigger is resolved to multiple watermarks in the pixel domain, which further improves watermark randomness, stealthiness, and resistance against Trojan detection. Extensive experiments show that LoneNeuron could escape state-of-the-art Trojan detectors. LoneNeuron~is also the first effective backdoor attack against vision transformers (ViTs).

Title: Detecting Missing-Permission-Check Vulnerabilities in Distributed Cloud Systems Abstract: ABSTRACTMissing- Permission-Check (MPC) vulnerability is a type of bug where permission checks are not enforced for privileged operations. MPC vulnerability is prevalent and can cause severe security impacts. This paper proposes the first tool to detect MPC vulnerabilities in distributed cloud systems. We conduct an in-depth study of 95 real-world MPC vulnerabilities and our findings motivate a new tool named MPChecker. The tool introduces a combined log-static analysis to automatically identify privileged operations by inferring variables representing user owned data and critical system states, whose accesses need to be protected. We have evaluated MPChecker with 6 popular distributed systems. The tool reports 44 new vulnerabilities, and 43 of them have been confirmed and labeled as critical bugs. Moreover, 1 bug is particular dangerous and the developers requested to keep it undisclosed.

Title: Proving UNSAT in Zero Knowledge Abstract: ABSTRACTZero-knowledge (ZK) protocols enable one party to prove to others that it knows a fact without revealing any information about the evidence for such knowledge. There exist ZK protocols for all problems in NP, and recent works developed highly efficient protocols for proving knowledge of satisfying assignments to Boolean formulas, circuits and other NP formalisms. This work shows an efficient protocol for the converse: proving formula unsatisfiability in ZK (when the prover posses a non-ZK proof). An immediate practical application is efficiently proving safety of secret programs. The key insight is to prove, in ZK, the validity of resolution proofs of unsatisfiability. This is efficiently realized using an algebraic representation that exploits resolution proofs' structure to represent formula clauses as low-degree polynomials, combined with ZK random-access arguments. Only the proof's dimensions are revealed. We implemented our protocol and used it to prove unsatisfiability of formulas that encode combinatoric problems and program correctness conditions in standard verification benchmarks, including Linux kernel drivers and Intel cryptography modules. The results demonstrate both that our protocol has practical utility, and that its aggressive optimizations, based on non-trivial encodings, significantly improve practical performance.

Title: Feature Inference Attack on Shapley Values Abstract: ABSTRACTAs a solution concept in cooperative game theory, Shapley value is highly recognized in model interpretability studies and widely adopted by the leading Machine Learning as a Service (MLaaS) providers, such as Google, Microsoft, and IBM. However, as the Shapley value-based model interpretability methods have been thoroughly studied, few researchers consider the privacy risks incurred by Shapley values, despite that interpretability and privacy are two foundations of machine learning (ML) models. In this paper, we investigate the privacy risks of Shapley value-based model interpretability methods using feature inference attacks: reconstructing the private model inputs based on their Shapley value explanations. Specifically, we present two adversaries. The first adversary can reconstruct the private inputs by training an attack model based on an auxiliary dataset and black-box access to the model interpretability services. The second adversary, even without any background knowledge, can successfully reconstruct most of the private features by exploiting the local linear correlations between the model inputs and outputs. We perform the proposed attacks on the leading MLaaS platforms, i.e., Google Cloud, Microsoft Azure, and IBM aix360. The experimental results demonstrate the vulnerability of the state-of-the-art Shapley value-based model interpretability methods used in the leading MLaaS platforms and highlight the significance and necessity of designing privacy-preserving model interpretability methods in future studies. To our best knowledge, this is also the first work that investigates the privacy risks of Shapley values.

Title: Securing Reset Operations in NISQ Quantum Computers Abstract: ABSTRACTA secure reset operation could be an enabling technology that allows sharing of a quantum computer among different users, or among different quantum programs of the same user. Today, the dominant method to erase the qubit state is a full system wipe, which effectively resets all the qubits at the same time. In today's superconducting qubit machines from IBM, for example, a full system wipe takes up to 1000 μs, and it fully erases all information in the system. However, with a full system wipe there is no means for only a few qubits to be cleared and assigned to a new user or program; everything has to be erased at the same time. A secure reset operation could allow resetting only a subset of qubits, and it could be built upon existing (insecure) reset operation available from superconducting qubit machines from IBM, for example. The (insecure) reset operation is available today, which can be used to reset the state of a qubit in a time on the order of 10 μs down to 1 μs. The reset operation is thus much faster than a full system wipe. However, as this work demonstrates, it is possible to leak some information across the (insecure) reset operation as it does not perfectly reset the qubit state between two users or programs who may be sequentially scheduled on the same qubit. Further, crosstalk-like effects are observed where reset behavior of one qubit can be inferred from an adjacent qubit. This work analyzes the existing (insecure) reset operation in order to understand how a secure reset operation could be built upon it. This work then describes the design, implementation, and evaluation of the proposed secure reset operation which can reset qubits without leaking information, and retains a factor of 300 speedup over a full system~wipe.

Title: Constant Latency in Sleepy Consensus Abstract: ABSTRACTDynamic participation support is an important feature of Bitcoin's longest-chain protocol and its variants. But these protocols suffer from long latency as a fundamental trade-off. Specifically, the latency depends at least on the following two factors: 1) the desired security level of the protocol, and 2) the actual participation level of the network. Classic BFT protocols, on the other hand, can achieve constant latency but cannot make progress under dynamic participation. In this work, we present a protocol that simultaneously supports dynamic participation and achieves constant latency. Our core technique is to extend the classic BFT approach from static quorum size to dynamic quorum size, i.e., according to the current participation level, while preserving important properties of static quorum. We also present a recovery mechanism for rejoining nodes that is efficient in terms of both communication and storage. Our experimental evaluation shows our protocol has much lower latency than a longest-chain protocol, especially when there is a sudden decrease of participation.

Title: Physical Hijacking Attacks against Object Trackers Abstract: ABSTRACTModern autonomous systems rely on both object detection and object tracking in their visual perception pipelines. Although many recent works have attacked the object detection component of autonomous vehicles, these attacks do not work on full pipelines that integrate object tracking to enhance the object detector's accuracy. Meanwhile, existing attacks against object tracking either lack real-world applicability or do not work against a powerful class of object trackers, Siamese trackers. In this paper, we present AttrackZone, a new physically-realizable tracker hijacking attack against Siamese trackers that systematically determines valid regions in an environment that can be used for physical perturbations. AttrackZone exploits the heatmap generation process of Siamese Region Proposal Networks in order to take control of an object's bounding box, resulting in physical consequences including vehicle collisions and masked intrusion of pedestrians into unauthorized areas. Evaluations in both the digital and physical domain show that AttrackZone achieves its attack goals 92% of the time, requiring only 0.3-3 seconds on average.

Title: The Multi-User Security of Triple Encryption, Revisited: Exact Security, Strengthening, and Application to TDES Abstract: ABSTRACTWe study the security of triple encryption in the multi-user setting with its application to Triple DES (TDES) in mind. Although depreciation of TDES is a global trend, the migration will take the next decade, considering the billions of TDES hardware the industry has invested so far. The multi-user security captures the reality of practical systems with multiple users, substantially impacts security, and is already considered in practical protocols such as TLS 1.3. The best multi-user lower bound of TDES is 43-(3/2) \cdot łog_2 u bits with u users, which is tractable with a standard PC and is unacceptably low. We devise a new proof to improve the multi-user security and show its tightness by giving a concrete attack. The new bound with the TDES parameters is 79-(1/2) \cdot łog_2 u bits. We also propose TEFX that strengthens triple encryption with the FX construction while preserving the compatibility with legacy hardware. TDES with TEFX achieves the multi-user security of 114-(1/2) \cdot łog_2 q bits with q TEFX calls: it achieves 84.5 bits with 2^40 users and 2^21 TEFX calls for each user, which is comparable to that of AES (128-40=88 bits).

Title: Sigstore: Software Signing for Everybody Abstract: ABSTRACTSoftware supply chain compromises are on the rise. From the effects of XCodeGhost to SolarWinds, hackers have identified that targeting weak points in the supply chain allows them to compromise high-value targets such as U.S. government agencies and corporate targets such as Google and Microsoft. Software signing, a promising mitigation for many of these attacks, has seen limited adoption in open-source and enterprise ecosystems. In this paper, we propose Sigstore, a system to provide widespread software signing capabilities. To do so, we designed the system to provide baseline artifact signing capabilities that minimize the adoption barrier for developers. To this end, Sigstore leverages three distinct mechanisms: First, it uses a protocol similar to ACME to authenticate developers through OIDC, tying signatures to existing and widely-used identities. Second, it enables developers to use ephemeral keys to sign their artifacts, reducing the inconvenience and risk of key management. Finally, Sigstore enables user authentication by means of artifact and identity logs, bringing transparency to software signatures. Sigstore is quickly becoming a critical piece of Internet infrastructure with more than 2.2M signatures over critical software such as Kubernetes and Distroless.