We say there is a share conversion from a secret-sharing scheme $\Pi$ to another scheme $\Pi'$ implementing the same access structure if each party can locally apply a deterministic function to their share to transform any valid secret-sharing under $\Pi$ to a valid (but not necessarily random) secret-sharing under $\Pi'$ of the same secret. If such a conversion exists, we say that $\Pi\ge\Pi'$. This notion was introduced by Cramer et al. (TCC'05), where they particularly proved that for any access structure, any linear secret-sharing scheme over a given field $\mathbb{F}$, has a conversion from a CNF scheme, and is convertible to a DNF scheme. In this work, we initiate a systematic study of convertability between secret-sharing schemes, and present a number of results with implications to the understanding of the convertibility landscape. - In the context of linear schemes, we present two key theorems providing necessary conditions for convertibility, proved using linear-algebraic tools. It has several implications, such as the fact that Shamir secret-sharing scheme can be neither maximal or minimal. Another implication of it is that a scheme may be minimal if its share complexity is at least as high as that of DNF. - Our second key result is a necessary condition for convertibility to CNF from a broad class of (not necessarily linear) schemes. This result is proved via information-theoretic techniques and implies non-maximality for schemes with share complexity smaller than that of CNF. We also provide a condition which is both necessary and sufficient for the existence of a share conversion to some linear scheme. The condition is stated as a system of linear equations, such that a conversion exists if and only if a solution to the linear system exists. We note that the impossibility results for linear schemes may be viewed as identifying a subset of contradicting equations in the system. Another contribution of our paper, is in defining and studying share conversion for evolving secret-sharing schemes. In such a schemes, recently introduced by Komargodski et al. (IEEE ToIT'18), the number of parties is not bounded apriori, and every party receives a share as it arrives, which never changes in the sequel. Our impossibility results have implications to the evolving setting as well. Interestingly, unlike in the standard setting, there is no maximum or minimum in a broad class of evolving schemes, even without any restriction on the share size. Finally, we show that, generally, there is no conversion between additive schemes over different fields, even from CNF to DNF! However by relaxing from perfect to statistical security, it may be possible to convert, and examplify this for (n,n)-threshold access structures.

Single Sign-On (SSO) is a popular authentication mechanism enabling users to access multiple web services with a single set of credentials. Despite its convenience, SSO faces outstanding privacy challenges. The Identity Provider (IdP) represents a single point of failure and can track users across different Relying Parties (RPs). Multiple colluding RPs may track users through common identity attributes. In response, anonymous credential-based SSO solutions have emerged to offer privacy-preserving authentication without revealing unnecessary user information. However, these solutions face two key challenges: supporting RP authentication without compromising user unlinkability and maintaining compatibility with the predominant Authorization Code Flow (ACF). This paper introduces VeriSSO, a novel SSO protocol based on verifiable credentials (VC) that supports RP authentication while preserving privacy and avoiding single points of failure. VeriSSO employs an independent authentication server committee to manage RP and user authentication, binding RP authentication with credential-based anonymous user authentication. This approach ensures user unlinkability while supporting RP authentication and allows RPs to continue using their existing verification routines with identity tokens as in the ACF workflow. VeriSSO's design also supports lawful de-anonymization, ensuring user accountability for misbehavior during anonymity. Experimental evaluations of VeriSSO demonstrate its efficiency and practicality, with authentication processes completed within 100 milliseconds.

A private-information-retrieval (PIR) scheme lets a client fetch a record from a remote database without revealing which record it fetched. Classic PIR schemes treat all database records the same but, in practice, some database records are much more popular (i.e., commonly fetched) than others. We introduce distributional PIR, a new type of PIR that can run faster than classic PIR---both asymptotically and concretely---when the popularity distribution is skewed. Distributional PIR provides exactly the same cryptographic privacy as classic PIR. The speedup comes from a relaxed form of correctness: distributional PIR guarantees that in-distribution queries succeed with good probability, while out-of-distribution queries succeed with lower probability. Because of its relaxed correctness, distributional PIR is best suited for applications where "best-effort" retrieval is acceptable. Moreover, for security, a client's decision to query the server must be independent of whether its past queries were successful. We construct a distributional-PIR scheme that makes black-box use of classic PIR protocols, and prove a lower bound on the server runtime of a natural class of distributional-PIR schemes. On two real-world popularity distributions, our construction reduces compute costs by $5$-$77\times$ compared to existing techniques. Finally, we build CrowdSurf, an end-to-end system for privately fetching tweets, and show that distributional-PIR reduces the end-to-end server cost by $8\times$.

This work introduces Private Eyes, the first zero-leakage biometric database. The only leakage of the system is unavoidable: 1) the log of the dataset size and 2) the fact that a query occurred. Private Eyes is built from oblivious symmetric searchable encryption. Approximate proximity queries are used: given a noisy reading of a biometric, the goal is to retrieve all stored records that are close enough according to a distance metric. Private Eyes combines locality sensitive-hashing or LSHs (Indyk and Motwani, STOC 1998) and oblivious maps which map keywords to values. One computes many LSHs of each record in the database and uses these hashes as keywords in the oblivious map with the matching biometric readings concatenated as the value. At search time with a noisy reading, one computes the LSHs and retrieves the disjunction of the resulting values from the map. The underlying oblivious map needs to answer disjunction queries efficiently. We focus on the iris biometric which requires a large number of LSHs, approximately $1000$. Boldyreva and Tang's (PoPETS 2021) design yields a suitable map for a small number of LSHs (their application was in zero-leakage $k$-nearest-neighbor search). Our solution is a zero-leakage disjunctive map designed for the setting when most clauses do not match any records. For the iris, on average at most $6\%$ of LSHs match any stored value. We evaluate using the ND-0405 dataset; this dataset has $356$ irises suitable for testing. To scale our evaluation, we use a generative adversarial network to produce synthetic irises. Accurate statistics on sizes beyond available datasets is crucial to optimizing the cryptographic primitives. This tool may be of independent interest. For the largest tested parameters of a $5000$ synthetic iris database, a search requires $18$ rounds of communication and $25$ms of parallel computation. Our scheme is implemented and open-sourced.

The Deligne-Ogus-Shioda theorem guarantees the existence of isomorphisms between products of supersingular elliptic curves over finite fields. In this paper, we present methods for explicitly computing these isomorphisms in polynomial time, given the endomorphism rings of the curves involved. Our approach leverages the Deuring correspondence, enabling us to reformulate computational isogeny problems into algebraic problems in quaternions. Specifically, we reduce the computation of isomorphisms to solving systems of quadratic and linear equations over the integers derived from norm equations. We develop $\ell$-adic techniques for solving these equations when we have access to a low discriminant subring. Combining these results leads to the description of an efficient probabilistic Las Vegas algorithm for computing the desired isomorphisms. Under GRH, it is proved to run in expected polynomial time.

The advancement of succinct non-interactive argument of knowledge (SNARK) with constant proof size has significantly enhanced the efficiency and privacy of verifiable computation. Verifiable computation finds applications in distributed computing networks, particularly in scenarios where nodes cannot be generally trusted, such as blockchains. However, fully harnessing the efficiency of SNARK becomes challenging when the computing targets in the network change frequently, as the SNARK verification can involve some untrusted preprocess of the target, which is expected to be reproduced by other nodes. This problem can be addressed with two approaches: One relieves the reproduction overhead by reducing the dimensionality of preprocessing data; The other utilizes verifiable machine computation, which eliminates the dependency on preprocess at the cost of increased overhead to SNARK proving and verification. In this paper, we propose a new SNARK with constant proof size applicable to both approaches. The proposed SNARK combines the efficiency of Groth16 protocol, albeit lacking universality for new problems, and the universality of PlonK protocol, albeit with significantly larger preprocessing data dimensions. Consequently, we demonstrate that our proposed SNARK maintains the efficiency and the universality while significantly reducing the dimensionality of preprocessing data. Furthermore, our SNARK can be seamlessly applied to the verifiable machine computation, requiring a proof size smaller about four to ten times than other related works.

Fruit-F is a lightweight short-state stream cipher designed by Ghafari et al. The authors designed this version of the cipher, after earlier versions of the cipher viz. Fruit 80/v2 succumbed to correlation attacks. The primary motivation behind this design seemed to be preventing correlation attacks. Fruit-F has a Grain-like structure with two state registers of size 50 bits each. In addition, the cipher uses an 80-bit secret key and an 80-bit IV. The authors use a complex key-derivation function to update the non-linear register which prevents the same key-bit alignment across fixed-length window of keystream bits, which is essentially what stops the correlation attacks. In this paper, we first present two attacks against Fruit-F. The first attack stems from the fact that the key-derivation can be rewritten as the Boolean xor of two key-dependent terms one of which is the Boolean OR of two bits of the key. Using this we show that the cipher does not offer 80-bit security: the effective key space of Fruit-F is slightly less than $2^{80}$, i.e. a simple brute force attack costs around $2^{80}-2^{49}$ time. The second is a differential attack using the cipher's complex initialization process. We show that under some given conditions, it is possible to have two initial vectors $V_1$ and $V_2$ that produce identical keystream vectors with any given key. Using this as a distinguisher, it is possible to collect enough linear and quadratic equations of the secret key to find it in practical time with very few keystream bits.

Evasive LWE (Wee, Eurocrypt 2022 and Tsabary, Crypto 2022) is a recently introduced, popular lattice assumption which has been used to tackle long-standing problems in lattice based cryptography. In this work, we develop new counter-examples against Evasive LWE, in both the private and public-coin regime, propose counter-measures that define safety zones, and finally explore modifications to construct full compact FE/iO. Attacks: Our attacks are summarized as follows. - The recent work by Hseih, Lin and Luo [HLL23] constructed the first ABE for unbounded depth circuits by relying on the (public coin) ''circular'' evasive LWE assumption, which incorporates circularity into the Evasive LWE assumption. We provide a new attack against this assumption by exhibiting a sampler such that the pre-condition is true but post-condition is false. - We demonstrate a counter-example against public-coin evasive LWE which exploits the freedom to choose the error distributions in the pre and post conditions. Our attack crucially relies on the error in the pre-condition being larger than the error in the post-condition. - The recent work by Agrawal, Kumari and Yamada [AKY24a] constructed the first functional encryption scheme for pseudorandom functionalities ($\mathsf{prFE}$) and extended this to obfuscation for pseudorandom functionalities ($\mathsf{prIO}$) [AKY24c] by relying on private-coin evasive LWE. We provide a new attack against the stated assumption. - The recent work by Branco et al. [BDJ+24] (concurrently to [AKY24c]) provides a construction of obfuscation for pseudorandom functionalities by relying on private-coin evasive LWE. By adapting the counter-example against [AKY24a], we provide an attack against this assumption. - Branco et al. [BDJ+24] showed that there exist contrived, somehow ''self-referential'', classes of pseudorandom functionalities for which pseudorandom obfuscation cannot exist. We develop an analogous result to the setting of pseudorandom functional encryption. While Evasive LWE was developed to specifically avoid zeroizing attacks as discussed above, our attacks show that in some (contrived) settings, the adversary may nevertheless obtain terms in the zeroizing regime. Counter-measures: Guided by the learning distilled from the above attacks, we develop counter-measures to prevent against them. Our interpretation of the above attacks is that Evasive LWE, as defined, is too general -- we suggest restrictions to identify safe zones for the assumption, using which, the broken applications can be recovered. Variants to give full FE and iO: Finally, we show that certain modifications of Evasive LWE, which respect the counter-measures developed above, yield full compact FE in the standard model. We caution that the main goal of presenting these candidates is as goals for cryptanalysis to further our understanding of this regime of assumptions.

ECDSA is a standard digital signature schemes that is widely used in TLS, Bitcoin and elsewhere. Unlike other schemes like RSA, Schnorr signatures and more, it is particularly hard to construct efficient threshold signature protocols for ECDSA (and DSA). As a result, the best-known protocols today for secure distributed ECDSA require running heavy zero-knowledge proofs and computing many large-modulus exponentiations for every signing operation. In this paper, we consider the specific case of two parties (and thus no honest majority) and construct a protocol that is approximately two orders of magnitude faster than the previous best. Concretely, our protocol achieves good performance, with a single signing operation for curve P-256 taking approximately 37ms between two standard machine types in Azure (utilizing a single core only). Our protocol is proven secure for sequential composition under standard assumptions using a game-based definition. In addition, we prove security by simulation under a plausible yet non-standard assumption regarding Paillier. We show that partial concurrency (where if one execution aborts then all need to abort) can also be achieved.

We demonstrate an attack on the soundness of a widely known optimization of the Gemini multilinear Polynomial Commitment Scheme (PCS). The attack allows a malicious prover to falsely claim that a multilinear polynomial takes a value of their choice, for any input point. We stress that the original Gemini multilinear PCS and HyperKZG, an adaptation of Gemini, are not affected by the attack.

We introduce MULTISS, a new distributed storage protocol over multiple remote Quantum Key Distribution (QKD) networks that ensures long-term data confidentiality. Our protocol extends LINCOS, a secure storage protocol that uses Shamir secret sharing to distribute data in a single QKD network. Instead MULTISS uses a hierarchical secret scheme that makes certain shares mandatory for the reconstruction of the original secret. We prove that MULTISS ensures that the stored data remain secure even if an eavesdropper (1) gets full access to all storage servers of some of the QKD networks or (2) stores and breaks later all the classical communication between the QKD networks. We demonstrate that this is strictly more secure than LINCOS which is broken as soon as one QKD network is compromised. Our protocol, like LINCOS, has a procedure to update the shares stored in each QKD network without reconstructing the original data. In addition, we provide a procedure to recover from a full compromission of one of the QKD network. In particular, we introduce a version of the protocol that can only be implemented over a restricted network topologies, but minimizes the communication required in the recovery procedure. In practice, the MULTISS protocol is designed for the case of several QKD networks at the metropolitan scale connected to each other through channels secured by classical cryptography. Hence, MULTISS offers a secure distributed storage solution in a scenario that is compatible with the current deployment of quantum networks.

Both masking and shuffling are very common software countermeasures against side-channel attacks. However, exploring possible combinations of the two countermeasures to increase and fine-tune side-channel resilience is less investigated. With this work, we aim to bridge that gap by both concretising the security guarantees of several masking and shuffling combinations presented in earlier work and additionally investigating their randomness cost. We subsequently implement these approaches to also analyse their performance. In this context, we present five different protected implementations of the new standard for lightweight cryptography, Ascon, on a 32-bit RISC-V architecture: A 3rd-order masked, unshuffled implementation and three combined 3rd-order masked and shuffled implementations. Additionally, we present a levelled implementation where only the particularly vulnerable keyed initialisation and finalisation of the permutation are masked and shuffled, while the rest is only shuffled. To further improve the security and performance of our implementations we make use of the Probe Isolating Non-Interference (PINI) masked AND gadget, coupled with techniques like bit-slicing and bit-interleaving. Utilising benchmarking and an MI-shortcut security analysis, we pinpoint the best masking-shuffling combinations that maximize security at reasonable overheads.

Making the most of TFHE advanced capabilities such as programmable or circuit bootstrapping and their generalizations for manipulating data larger than the native plaintext domain of the scheme is a very active line of research. In this context, AES is a particularly interesting benchmark, as an example of a nontrivial algorithm which has eluded "practical" FHE execution performances for years, as well as the fact that it will most likely be selected by NIST as a flagship reference in its upcoming call on threshold (homomorphic) cryptography. Since 2023, the algorithm has thus been the subject of a renewed attention from the FHE community and has served as a playground to test advanced operators following the LUT-based, $p$-encodings or several variants of circuit bootstrapping, each time leading to further timing improvements. Still, AES is also interesting as a benchmark because of the tension between boolean- and byte-oriented operations within the algorithm. In this paper, we resolve this tension by proposing a new approach, coined "Hippogryph", which consistently combines the (byte-oriented) LUT-based approach with a generalization of the (boolean-oriented) $p$-encodings one to get the best of both worlds. In doing so, we obtain the best timings so far, getting a single-core execution of the algorithm over TFHE from 46 down to 32 seconds and approaching the 1 second barrier with only a mild amount of parallelism. We should also stress that all the timings reported in this paper are consistently obtained on the same machine which is often not the case in previous studies. Lastly, we emphasize that the techniques we develop are applicable beyond just AES since the boolean-byte tension is a recurrent issue when running algorithms over TFHE.

The conversion between arithmetic and Boolean masking representations (A2B \& B2A) is a crucial component for side-channel resistant implementations of lattice-based (post-quantum) cryptography. In this paper, we first propose novel $d$-order algorithms for the secure addition (SecADDChain$_q$) and B2A (B2X2A). Our secure adder is well-suited for repeated ('chained') executions, achieved through an improved method for repeated masked modular reduction. The optimized B2X2A gadget removes a full secure addition compared to state-of-the-art B2A approaches, by relying on the X2B operation. This component directly converts a compositely shared variable, consisting of a mix of arithmetic and Boolean sharing, to $d+1$ Boolean shares. This approach reduces the required amount of SecADDs to $2d$, of which $2\cdot\lceil\text{log}_2(d)\rceil$ are max-order. Secondly, we develop both a first- and high-order masked, unified hardware implementation that can compute both A2B & B2A conversions for power-of-two ($p$) and prime ($q$) moduli. Compared to state-of-the-art (high-throughput) hardware implementations that only support A2B$_k$, we reduce area utilization for a second-order implementation by 45% up to 60% and fresh randomness up to 62%, while supporting all four types of additive mask conversions. Our first-order design only requires 1,133/2,170 [LUT/FF] on Kintex-7 FPGAs. Our proposed algorithms are proven secure in the robust probing model and their implementations are validated via practical lab analysis using the TVLA methodology. We experimentally show that our masked implementation is hardened against first-and second order univariate and multivariate power-based side-channel attacks using 100 million traces, for each mode of operation.

zk-SNARK constructions that utilize an updatable universal structured reference string remove one of the main obstacles in deploying zk-SNARKs [GKMMM, Crypto 2018]. The important work of Maller et al. [MBKM, CCS 2019] presented $\mathsf{Sonic}$ - the first potentially practical zk-SNARK with fully succinct verification for general arithmetic circuits with such an SRS. However, the version of $\mathsf{Sonic}$ enabling fully succinct verification still requires relatively high proof construction overheads. We present a universal SNARK construction with fully succinct verification, and significantly lower prover running time (roughly 7.5-20 less group exponentiations than [MBKM] in the fully succinct verifier mode depending on circuit structure). Similarly to [MBKM], we rely on a permutation argument based on Bayer and Groth [Eurocrypt 2012]. However, we focus on ``Evaluations on a subgroup rather than coefficients of monomials''; which enables simplifying both the permutation argument and the artihmetization step.

In this paper, we propose the Differential Fault Attack (DFA) on three Homomorphic Encryption (HE) friendly stream ciphers \textsf{Masta}, \textsf{Pasta}, and \textsf{Elisabeth}. Both \textsf{Masta} and \textsf{Pasta} are \textsf{Rasta}-like ciphers with publicly derived and pseudorandom affine layers. The design of \textsf{Elisabeth} is an extension of \textsf{FLIP} and \textsf{FiLIP}, following the group filter permutator paradigm. All these three ciphers operate on elements over $\mathbb{Z}_p$ or $\mathbb{Z}_{2^n}$, rather than $\mathbb{Z}_2$. We can recover the secret keys of all the targeted ciphers through DFA. In particular, for \textsf{Elisabeth}, we present a new method to determine the filtering path, which is vital to make the attack practical. Our attacks on various instances of \textsf{Masta} are practical and require only one block of keystream and a single word-based fault. By injecting three word-based faults, we can theoretically mount DFA on two instances of \textsf{Pasta}, \textsf{Pasta}-3 and \textsf{Pasta}-4. For \textsf{Elisabeth}-4, the only instance of the \textsf{Elisabeth} family, we present two DFAs in which we inject four bit-based faults or a single word-based fault. With 15000 normal and faulty keystream words, the DFA on \textsf{Elisabeth}-4 can be completed in just a few minutes.

Since the selection of the National Institute of Standards and Technology (NIST) Post-Quantum Cryptography (PQC) standardization algorithms, research on integrating PQC into security protocols such as TLS/SSL, IPSec, and DNSSEC has been actively pursued. However, PQC migration for Internet of Things (IoT) communication protocols remains largely unexplored. Embedded devices in IoT environments have limited computational power and memory, making it crucial to optimize PQC algorithms for efficient computation and minimal memory usage when deploying them on low-spec IoT devices. In this paper, we introduce KEM-MQTT, a lightweight and efficient Key Encapsulation Mechanism (KEM) for the Message Queuing Telemetry Transport (MQTT) protocol, widely used in IoT environments. Our approach applies the NIST KEM algorithm Crystals-Kyber (Kyber) while leveraging MQTT’s characteristics and sensor node constraints. To enhance efficiency, we address certificate verification issues and adopt KEMTLS to eliminate the need for Post-Quantum Digital Signatures Algorithm (PQC-DSA) in mutual authentication. As a result, KEM-MQTT retains its lightweight properties while maintaining the security guarantees of TLS 1.3. We identify inefficiencies in existing Kyber implementations on 8-bit AVR microcontrollers (MCUs), which are highly resource-constrained. To address this, we propose novel implementation techniques that optimize Kyber for AVR, focusing on high-speed execution, reduced memory consumption, and secure implementation, including Signed LookUp-Table (LUT) Reduction. Our optimized Kyber achieves performance gains of 81%,75%, and 85% in the KeyGen, Encaps, and DeCaps processes, respectively, compared to the reference implementation. With approximately 3 KB of stack usage, our Kyber implementation surpasses all state-of-the-art Elliptic Curve Diffie-Hellman (ECDH) implementations. Finally, in KEM-MQTT using Kyber-512, an 8-bit AVR device completes the handshake preparation process in 4.32 seconds, excluding the physical transmission and reception times.

We show that the certificateless authentication scheme [Mob. Networks Appl. 2022, 27, 346-356] fails to keep anonymity, not as claimed. The scheme neglects the basic requirement for bit-wise XOR, and tries to encrypt data by the operator. The negligence results in some trivial equalities. The adversary can retrieve the user's identity from one captured string via the open channel.

Current hardware security verification processes predominantly rely on manual threat modeling and test plan generation, which are labor-intensive, error-prone, and struggle to scale with increasing design complexity and evolving attack methodologies. To address these challenges, we propose ThreatLens, an LLM-driven multi-agent framework that automates security threat modeling and test plan generation for hardware security verification. ThreatLens integrates retrieval-augmented generation (RAG) to extract relevant security knowledge, LLM-powered reasoning for threat assessment, and interactive user feedback to ensure the generation of practical test plans. By automating these processes, the framework reduces the manual verification effort, enhances coverage, and ensures a structured, adaptable approach to security verification. We evaluated our framework on the NEORV32 SoC, demonstrating its capability to automate security verification through structured test plans and validating its effectiveness in real-world scenarios.

This work presents an exact and compact formula for the probability of rotation-xor differentials (RX-differentials) through modular addition, for arbitrary rotation amounts, which has been a long-standing open problem. The formula comes with a rigorous proof and is also verified by extensive experiments. Our formula uncovers error in a recent work from 2022 proposing a formula for rotation amounts bigger than 1. Surprisingly, it also affects correctness of the more studied and used formula for the rotation amount equal to 1 (from TOSC 2016). Specifically, it uncovers rare cases where the assumptions of this formula do not hold. Correct formula for arbitrary rotations now opens up a larger search space where one can often find better trails. For applications, we propose automated mixed integer linear programming (MILP) modeling techniques for searching optimal RX-trails based on our exact formula. They are consequently applied to several ARX designs, including Salsa, Alzette and a small-key variant of Speck, and yield many new RX-differential distinguishers, some of them based on provably optimal trails. In order to showcase the relevance of the RX-differential analysis, we also design Malzette, a 12-round Alzette-based permutation with maliciously chosen constants, which has a practical RX-differential distinguisher, while standard differential/linear security arguments suggest sufficient security.

Deep learning-based side-channel analysis has become a popular and powerful option for side-channel attacks in recent years. One of the main directions that the side-channel community explores is how to design efficient architectures that can break the targets with as little as possible attack traces, but also how to consistently build such architectures. In this work, we explore the usage of the JumpReLU activation function, which was designed to improve the robustness of neural networks. Intuitively speaking, improving the robustness seems a natural requirement for side-channel analysis, as hiding countermeasures could be considered adversarial attacks. In our experiments, we explore three strategies: 1) exchanging the activation functions with JumpReLU at the inference phase, training common side-channel architectures with JumpReLU, and 3) conducting hyperparameter search with JumpReLU as the activation function. While the first two options do not yield improvements in results (but also do not show worse performance), the third option brings advantages, especially considering the number of neural networks that break the target. As such, we conclude that using JumpReLU is a good option to improve the stability of attack results.

In this paper, we present a side-channel attack on the hardware AES accelerator of a Bluetooth chip used in millions of devices worldwide, ranging from wearables and smart home products to industrial IoT. The attack leverages information about AES computations unintentionally transmitted by the chip together with RF signals to recover the encryption key. Unlike traditional side-channel attacks that rely on power or near-field electromagnetic emissions as sources of information, RF-based attacks leave no evidence of tampering, as they do not require package removal, chip decapsulation, or additional soldered components. However, side-channel emissions extracted from RF signals are considerably weaker and noisier, necessitating more traces for key recovery. The presented profiled machine learning-assisted attack can recover the full encryption key from 90,000 traces captured at a one-meter distance from the target device, with each trace being an average of 10,000 samples per encryption. This is a twofold improvement over the correlation analysis-based attack on the same AES accelerator.

Content-defined chunking (CDC) algorithms split streams of data into smaller blocks, called chunks, in a way that preserves chunk boundaries when the data is partially changed. CDC is ubiquitous in applications that deduplicate data such as backup solutions, software patching systems, and file hosting platforms. Much like compression, CDC can introduce leakage when combined with encryption: fingerprinting attacks can exploit chunk length patterns to infer information about the data. To address these risks, many systems—mainly in the cloud backup setting—have developed bespoke mitigations by mixing a cryptographic key into the chunking process. We study these keyed CDC (KCDC) schemes “in the wild”, presenting efficient key recovery attacks against five different KCDC schemes, deployed in the backup solutions Borg, Bupstash, Duplicacy, Restic, and Tarsnap. Our attacks are in a realistic threat model that relies only on weak known or chosen-plaintext capabilities. This shows, in particular, that they fail to protect against fingerprinting attacks. To demonstrate practical exploitability, we also present “end-to-end” attacks on three complete encrypted backup applications, namely Borg, Restic and Tarsnap. These build on our attacks on the underlying KCDC schemes. In an effort to tackle these problems, we introduce the first formal treatment for KCDC schemes and propose a provably secure construction that fulfills a strong notion of security. We benchmark our construction against existing (broken) approaches, showing that it has competitive performance. In doing so, we take a step towards making real-world systems that rely on KCDC more resilient to attacks.

Distributed SNARKs enable multiple provers to collaboratively generate proofs, enhancing the efficiency and scalability of large-scale computations. The state-of-the-art distributed SNARK for Plonk, Pianist (S\&P '24), achieves constant proof size, constant amortized communication complexity, and constant verifier complexity. However, when proving the Rank-One Constraint System (R1CS), a widely used intermediate representation for SNARKs, Pianist must perform the transformation from R1CS into Plonk before proving, which can introduce a start-up cost of $10\times$ due to the expansion of the statement size. Meanwhile, existing distributed SNARKs for R1CS, e.g., DIZK (USENIX Sec. '18) and Hekaton (CCS '24), fail to match the superior asymptotic complexities of Pianist. We propose $\textsf{Soloist}$, an optimized distributed SNARK for R1CS. $\textsf{Soloist}$ achieves constant proof size, constant amortized communication complexity, and constant verifier complexity, relative to the R1CS size $n$. Utilized with $\ell$ sub-provers, its prover complexity is $O(n/\ell \cdot \log(n/\ell))$. The concrete prover time is~$\ell\times$ as fast as the R1CS-targeted Marlin (Eurocrypt '20). For zkRollups, $\textsf{Soloist}$ can prove more transactions, with $2.5 \times$ smaller memory costs, $2.8\times$ faster preprocessing, and $1.8\times$ faster proving than Pianist. $\textsf{Soloist}$ leverages an improved inner product argument and a new batch bivariate polynomial commitment variant of KZG (Asiacrypt '10). To achieve constant verification, we propose a new preprocessing method with a lookup argument for unprescribed tables, which are usually assumed pre-committed in prior works. Notably, all these schemes are equipped with scalable distributed mechanisms.

In this paper, we present a new efficient stand-alone MAC construct named SMAC, based on processing using the Finite State Machine (FSM) part of the stream cipher family SNOW, which in turn uses the AES round function. It offers a combination of very high speed in software and hardware with a truncatable tag. Three concrete base versions of SMAC are proposed, each offering a different security level. SMAC can also be directly integrated with an external ciphering engine in an AEAD mode. Every design decision is thoroughly justified and supported by the results of our cryptanalysis and simulations. Additionally, we introduce an aggregated mode version, SMAC-1$\times n$, in which software performance reaches up to 925 Gbps (around 0.038 cycles per byte) for long messages in a single thread. To the best of our knowledge, SMAC achieves a record-breaking software performance compared to all known MAC engines.

In order for a client to securely connect to a server on the web, the client must trust certificate authorities (CAs) only to issue certificates to the legitimate operator of the server. If a certificate is miss-issued, it is possible for an attacker to impersonate the server to the client. The goal of Certificate Transparency (CT) is to log every certificate issued in a manner that allows anyone to audit the logs for miss-issuance. A client can even audit a CT log itself, but this would leak sensitive browsing data to the log operator. As a result, client-side audits are rare in practice. In this work, we revisit private CT auditing from a real-world perspective. Our study is motivated by recent changes to the CT ecosystem and advancements in Private Information Retrieval (PIR). First, we find that checking for inclusion of Signed Certificate Timestamps (SCTs) in a log — the audit performed by clients — is now possible with PIR in under a second and under 100kb of communication with minor adjustments to the protocol that have been proposed previously. Our results also show how to scale audits by using existing batching techniques and the algebraic structure of the PIR protocols, in particular to obtain certificate hashes by included in the log. Since PIR protocols are more performant with smaller databases, we also suggest a number of strategies to lower the size of the SCT database for audits. Our key observation is that the web will likely transition to a new model for certificate issuance. While this transition is primarily motivated by the need to adapt the PKI to larger, post-quantum signature schemes, it also removes the need for SCT audits in most cases. We present the first estimates of how this transition may impact SCT auditing, based on data gathered from public CT logs. We find that large scale deployment of the new issuance model may reduce the number of SCT audits needed by a factor of 1,000, making PIR-based auditing practical to deploy.

Identity-based matchmaking encryption (IB-ME) [Ateniese et al., Crypto 2019] allows users to communicate privately, anonymously, and authentically. After the seminal paper by Ateniese et al., much work has been done on the security and construction of IB-ME. In this work, we revisit the security definitions of IB-ME and provide improved constructions. First, we classify the existing security notions of IB-ME, systematically categorizing privacy into three categories (CPA, CCA, and privacy in the case of mismatch) and authenticity into four categories (NMA and CMA, both against insiders and outsiders). In particular, we reconsider privacy when the sender's identity is mismatched during decryption and provide a new simple security game called mismatch security, capturing its essence. Second, we propose efficient and strongly secure IB-ME schemes from the bilinear Diffie-Hellman assumption in the random oracle model and from anonymous identity-based encryption and identity-based signature in the quantum random oracle model. The first scheme is based on Boneh-Franklin IBE, similar to the Ateniese et al. scheme, but ours achieves a more compact decryption key and ciphertext and stronger CCA-privacy, CMA-authenticity, and mismatch security. The second scheme is an improved generic construction, which achieves not only stronger security but also the shortest ciphertext among existing generic constructions. This generic construction provides a practical scheme from lattices in the quantum random oracle model.

We describe Crescent, a construction and implementation of privacy-preserving credentials. The system works by upgrading the privacy features of existing credentials, such as JSON Web Tokens (JWTs) and Mobile Driver's License (mDL) and as such does not require a new party to issue credentials. By using zero-knowledge proofs of possession of these credentials, we can add privacy features such as selective disclosure and unlinkability, without help from credential issuers. The system has practical performance, offering fast proof generation and verification times (tens of milliseconds) after a once-per-credential setup phase. We give demos for two practical scenarios, proof of employment for benefits eligibility (based on an employer-issued JWT), and online age verification (based on an mDL). We provide an open-source implementation to enable further research and experimentation. This paper is a draft describing our work, aiming to include enough material to describe the functionality, and some details of the internals of our new library, available at https://github.com/microsoft/crescent-credentials.

We initiate the study of strong federated authentication with password-based credential against identity server corruption (SaPBC). We provide a refined formal security model, which captures all the necessary security properties in registration, authentication, and session key establishment between a user and an application server. The new model with fine-grained information leakage separates the leakage of password-related files and long-term secrets (including passwords and credentials). Moreover, we present two SaPBC protocols constructed from efficient cryptographic primitives for these corruption scenarios. In addition to rigorous security proofs, we also conduct comprehensive performance evaluation of the two protocols.

Oblivious permutation (OP) enables two parties, a sender with a private data vector $x$ and a receiver with a private permutation π, to securely obtain the shares of π(x). OP has been used to construct many important MPC primitives and applications such as secret shuffle, oblivious sorting, private set operations, secure database analysis, and privacy-preserving machine learning. Due to its high complexity, OP has become a performance bottleneck in several practical applications, and many efforts have been devoted to enhancing its concrete efficiency. Chase et al. (Asiacrypt'20) proposed an offline-online OP paradigm leveraging a pre-computable resource termed Share Translation. While this paradigm significantly reduces online costs, the substantial offline cost of generating Share Translation remains an area for further investigation. In this work, we redefine the pre-computable resource as a cryptographic primitive known as Correlated Oblivious Permutation (COP) and conduct in-depth analyses and optimizations of the two COP generation solutions: network-based solution and matrix-based solution. The optimizations for the network-based solution halve the communication/computation cost of constructing a switch (the basic unit of the permutation network) and reduce the number of switches in the permutation network. The optimizations for the matrix-based solution halve the communication cost of small-size COP generation and reduce the cost of large-size COP generation with in-outside permutation decomposition. We implement our two COP generation protocols and conduct comprehensive evaluations. Taking commonly used 128-bit input data as an example, our network-based and matrix-based solutions are up to 1.7x and 1.6x faster than baseline protocols, respectively. We further facilitate the state-of-the-art (SOTA) PSU protocols with our optimized COP, achieving over 25% reduction in communication cost and 35% decrease in execution time. This shows that our COP optimizations bring significant improvements for real-world MPC primitives.

In recent years, the integration of deep learning with differential cryptanalysis has led to differential neural cryptanalysis, enabling efficient data-driven security evaluation of modern cryptographic algorithms. Compared to traditional differential cryptanalysis, differential neural cryptanalysis enhances the efficiency and automation of the analysis by training neural networks to automatically extract statistical features from ciphertext pairs. As research advances, neural distinguisher construction faces challenges due to the absence of a unified framework capable of cross-algorithm generalization and feature optimization. There's no systematic way to build a framework from data formats and network architectures, which limits their scalability across diverse ciphers and and their suitability for combining different cryptanalysis methods. While neural network training is data-driven, we lack interpretable explanations for the quality of differentially generated datasets. Therefore, there is an urgent need to combine cryptographic theory with data analysis methods to systematically evaluate dataset quality. This paper proposes a novel framework for constructing related-key neural differential distinguishers that integrates three core innovations: (1) multi-ciphertext multi-difference formats to enhance dataset diversity and feature coverage, (2) structural filtering for prioritizing high-probability differential paths aligned with cryptographic architectures, and (3) Deep Residual Shrinkage Network (DRSN) with adaptive thresholding to suppress noise and amplify critical differential features. By applying this framework to two standardized algorithms DES and PRESENT, our results demonstrate significant advancements. For DES, the framework achieves an 8-round related-key neural distinguisher and improves 6/7-round distinguisher accuracy by over 40%. For PRESENT, we construct the first 9-round related-key neural distinguisher, which outperforms existing neutral distinguishers in both round coverage and accuracy. Additionally, we employ kernel principal component analysis (KPCA) and K-means clustering to evaluate the quality of differential datasets for DES and PRESENT, revealing that clustering compactness strongly correlates with distinguisher performance. Furthermore, we propose a validation algorithm to verify differential combinations with cryptographic advantages from a machine learning perspective, identifying ‘good’ plaintext-key differential combinations. We apply this approach to the SIMECK algorithm, demonstrating its broad applicability. These findings validate the framework’s effectiveness in bridging cryptographic analysis with data-driven feature extraction and offer new insights for automated security evaluation of block ciphers.

In parallel with the standardization of lattice-based cryptosystems, the research community in Post-quantum Cryptography focused on non-lattice-based hard problems for constructing public-key cryptographic primitives. The Linear Code Equivalence (LCE) Problem has gained attention regarding its practical applications and cryptanalysis. Recent advancements, including the LESS signature scheme and its candidacy in the NIST standardization for additional signatures, supported LCE as a foundation for post-quantum cryptographic primitives. However, recent cryptanalytic results have revealed vulnerabilities in LCE-based constructions when multiple related public keys are available for one specific code rate. In this work, we generalize the proposed attacks to cover all code rates. We show that the complexity of recovering the private key from multiple public keys is significantly reduced for any code rate scenario. Thus, we advise against constructing specific cryptographic primitives using LCE.

We analyze the composition of symmetric encryption and digital signatures in secure group messaging protocols where group members share a symmetric encryption key. In particular, we analyze the chat encryption algorithms underlying MLS, Session, Signal, and Matrix using the formalism of symmetric signcryption introduced by Jaeger, Kumar, and Stepanovs (Eurocrypt 2024). We identify theoretical attacks against each of the constructions we analyze that result from the insufficient binding between the symmetric encryption scheme and the digital signature scheme. In the case of MLS and Session, these translate into practically exploitable replay and reordering attacks by a group-insider. For Signal this leads to a forgery attack by a group-outsider with access to a user’s signing key, an attack previously discovered by Balbás, Collins, and Gajland (Asiacrypt 2023). In Matrix there are mitigations in the broader ecosystem that prevent exploitation. We provide formal security theorems that each of the four constructions are secure up to these attacks. Additionally, in Session we identified two attacks outside the symmetric signcryption model. The first allows a group-outsider with access to an exposed signing key to forge arbitrary messages and the second allows outsiders to replay ciphertexts.

Hardware IP blocks have been subjected to various forms of confidentiality and integrity attacks in recent years due to the globalization of the semiconductor industry. System-on-chip (SoC) designers are now considering a zero-trust model for security, where an IP can be attacked at any stage of the manufacturing process for piracy, cloning, overproduction, or malicious alterations. Hardware redaction has emerged as a promising countermeasure to thwart confidentiality and integrity attacks by untrusted entities in the globally distributed supply chain. However, existing redaction techniques provide this security at high overhead costs, making them unsuitable for real-world implementation. In this paper, we propose HIPR, a fine-grain redaction methodology that is robust, scalable, and incurs significantly lower overhead compared to existing redaction techniques. HIPR redacts security-critical Boolean and sequential logic from the hardware design, performs interconnect randomization, and employs multiple overhead optimization steps to reduce overhead costs. We evaluate HIPR on open-source benchmarks and reduce area overheads by 1 to 2 orders of magnitude compared to state-of-the-art redaction techniques without compromising security. We also demonstrate that the redaction performed by HIPR is resilient against conventional functional and structural attacks on hardware IPs. The redacted test IPs used to evaluate HIPR are available at: https://github.com/UF-Nelms-IoT-Git-Projects/HIPR.

A (single server) private information retrieval (PIR) allows a client to read data from a public database held on a remote server, without revealing to the server which locations she is reading. In a doubly efficient PIR (DEPIR), the database is first preprocessed offline into a data structure, which then allows the server to answer any client query efficiently in sub-linear online time. Constructing DEPIR is a notoriously difficult problem, and this difficulty even extends to a weaker notion secret-key DEPIR (SK-DEPIR), where the database is preprocessed using secret randomness and the client is given a secret key for making queries. We currently only have constructions of SK-DEPIR from the Ring LWE assumption or from non-standard code-based assumptions. We show that the black-box use of essentially all generic cryptographic primitives (e.g., key agreement, oblivious transfer, indistinguishability obfuscation, etc.), including idealized primitives (e.g., random oracles, generic multilinear groups, virtual black-box obfuscation, etc.) is essentially useless for constructing SK-DEPIR. In particular, in any such SK-DEPIR construction, we can replace all black-box use of these primitives with just a black-box use of one-way functions. While we conjecture that SK-DEPIR cannot be constructed using black-box one-way functions alone, we are unable to show this in its full generality. However, we do show this for 2-round schemes with a passive server that simply outputs requested locations in the preprocessed data structure, which is the format of all known schemes. Overall, this shows that the black-box use of essentially all crypto primitives is insufficient for constructing 2-round passive-server SK-DEPIR, and does not provide any benefit beyond black-box one-way functions for constructing general SK-DEPIR.

Lookup arguments have recently attracted a lot of developments due to their applications in the constructions of succinct non-interactive arguments of knowledge (SNARKs). A closely related topic is subsequence arguments in which one can prove that string $\mathbf{s}$ is a subsequence of another string $\mathbf{t}$, i.e., deleting some characters in $\mathbf{t}$ can achieve $\mathbf{s}$. A dual notion, namely, non-subsequence arguments, is to prove that $\mathbf{s}$ is not a subsequence of $\mathbf{t}$. These problems have a lot of important applications in DNA sequence analysis, internet of things, blockchains, natural language processing, speech recognition, etc. However, despite their applications, they are not well-studied in cryptography, especially succinct arguments for non-subsequences with efficient proving time and sublinear verification time. In this work, we propose the first succinct non-subsequence argument. Our solution applies the sumcheck protocol and is instantiable by any multivariate polynomial commitment schemes (PCSs). We achieve an efficient prover whose running time is linear in the size of sequences $\mathbf{s}$, $\mathbf{t}$ and their respective alphabet $\Sigma$. Our proof is succinct and the verifier time is sublinear assuming the employed PCS has succinct commitments and sublinear verification time. When instantiating with Sona PCS (EUROCRYPT'24), we achieve proof size $\mathcal{O}(\log_2|\mathbf{s}| + \log_2|\mathbf{t}|+\log_2|\Sigma|)$, prover time $\mathcal{O}(|\mathbf{s}|+|\mathbf{t}|+|\Sigma|)$ and verifier time $\mathcal{O}(\sqrt{|\mathbf{s}|}+\sqrt{|\mathbf{t}|}+\sqrt{|\Sigma|})$. Extending our technique, we can achieve a batch subsequence argument for proving in batch $k$ interleaving subsequence and non-subsequence arguments without proof size suffering a linear blow-up in $k$.

Ever since the introduction of encryption, society has been divided over whether the government (or law enforcement agencies) should have the capability to decrypt private messages (with or without a war- rant) of its citizens. From a technical viewpoint, the folklore belief is that semantic security always enables some form of steganography. Thus, adding backdoors to semantically secure schemes is pointless: it only weakens the security of the “good guys”, while “bad guys” can easily circumvent censorship, even if forced to hand over their decryption keys. In this paper we put a dent in this folklore. We formalize three worlds: Dictatoria (“dictator wins”: no convenient steganography, no user co- operation needed), Warrantland (“checks-and-balances”: no convenient steganography, but need user’s cooperation) and Privatopia (“privacy wins”: built-in, high-rate steganography, even if giving away the decryption key). We give strong evidence that all these worlds are possible, thus reopening the encryption debate on a technical level. Our main novelty is the definition and design of special encryption schemes we call anamorphic-resistant (AR). In contrast to so called “anamorphic schemes”, — which were studied in the literature and form the basis of Privatopia, — any attempt to steganographically communicate over an AR-encryption scheme will be either impossible or hugely slow (depending on the definitional details).

This paper examines whether a revocation function can be added to a protocol, protocol FSU, which is an asymmetric pairing variant of a protocol that has been adopted as an international standard, ISO/IEC11770-3. Protocol FSU is an identity-based authenticated-key exchange protocol based on a mathematical problem, an asymmetric gap bilinear Diffie--Hellman (GBDH) problem. To make protocol FSU revocable, a generic technique is applied, which converts an identity-based encryption scheme to a revocable identity-based encryption scheme by introducing a symmetric-key encryption scheme. In addition, to make the converted revocable identity-based authenticated-key exchange protocol efficient, we reduce ephemeral information exchanged in the protocol, and introduce an additional parameter to the master public-key where the secret information of the additional parameter is not needed to include in the master secret-key. We discuss the security of the resultant protocol, and prove that it is rid-eCK secure under the asymmetric GBDH assumption.

In a social key recovery scheme, users back up their secret keys (typically using Shamir's secret sharing) with their social connections, known as a set of guardians. This places a heavy burden on the guardians, as they must manage their shares both securely and reliably. Finding and managing such a set of guardians may not be easy, especially when the consequences of losing a key are significant. We take an alternative approach of social recovery within a community, where each member already holds a secret key (with possibly an associated public key) and uses other community members as their guardians forming a mutual dependency among themselves. Potentially, each member acts as a guardian for upto $(n-1)$ other community members. Therefore, in this setting, using standard Shamir's sharing leads to a linear ($O(n)$) blow-up in the internal secret storage of the guardian for each key recovery. Our solution avoids this linear blowup in internal secret storage by relying on a novel secret-sharing scheme, leveraging the fact that each member already manages a secret key. In fact, our scheme does not require guardians to store anything beyond their own secret keys. We propose the first formal definition of a social key recovery scheme for general access structures in the community setting. We prove that our scheme is secure against any malicious and adaptive adversary that may corrupt up to $t$ parties. As a main technical tool, we use a new notion of secret sharing, that enables $(t+1)$ out of $n$ sharing of a secret even when the shares are generated independently -- we formalize this as bottom-up secret sharing (BUSS), which may be of independent interest. Finally, we provide an implementation benchmarking varying the number of guardians both in a regional, and geo-distributed setting. For instance, for 8 guardians, our backup protocol takes around 146-149 ms in a geo-distributed WAN setting, and 4.9-5.9 ms in the LAN setting; for recovery protocol, the timings are approximately the same for the WAN setting (as network latency dominates), and 1.2-1.4 ms for the LAN setting.

Large Language Models (LLMs) have emerged as powerful tools across various domains within cyber security. Notably, recent studies are increasingly exploring LLMs applied to the context of blockchain security (BS). However, there remains a gap in a comprehensive understanding regarding the full scope of applications, impacts, and potential constraints of LLMs on blockchain security. To fill this gap, we undertake a literature review focusing on the studies that apply LLMs in blockchain security (LLM4BS). Our study aims to comprehensively analyze and understand existing research, and elucidate how LLMs contribute to enhancing the security of blockchain systems. Through a thorough examination of existing literature, we delve into the integration of LLMs into various aspects of blockchain security. We explore the mechanisms through which LLMs can bolster blockchain security, including their applications in smart contract auditing, transaction anomaly detection, vulnerability repair, program analysis of smart contracts, and serving as participants in the cryptocurrency community. Furthermore, we assess the challenges and limitations associated with leveraging LLMs for enhancing blockchain security, considering factors such as scalability, privacy concerns, and ethical concerns. Our thorough review sheds light on the opportunities and potential risks of tasks on LLM4BS, providing valuable insights for researchers, practitioners, and policymakers alike.

Digital identity wallets allow citizens to prove who they are and manage digital documents, called credentials, such as mobile driving licenses or passports. As with physical documents, secure and privacy-preserving management of the credential lifecycle is crucial: a credential can change its status from issued to valid, revoked or expired. In this paper, we focus on the analysis of cryptographic accumulators as a revocation scheme for digital identity wallet credentials. We describe the most well-established public key accumulators, and how zero-knowledge proofs can be used with accumulators for revocation of non-anonymous credentials. In addition, we assess the computational and communication costs analytically and experimentally. Our results show that they are comparable with existing schemes used in the context of certificate revocation.

HAWK is a lattice-based signature scheme candidate to the fourth call of the NIST's Post-Quantum standardization campaign. Considered as a cousin of Falcon (one of the future NIST post-quantum standards) one can wonder whether HAWK shares the same drawbacks as Falcon in terms of side-channel attacks. Indeed, Falcon signature algorithm and particularly its Gaussian sampler, has shown to be highly vulnerable to power-analysis attacks. Besides, efficiently protecting Falcon's signature algorithm against these attacks seems a very challenging task. This work presents the first power analysis leakage review on HAWK signature scheme: it extensively assesses the vulnerabilities of a central and sensitive brick of the scheme, the discrete Gaussian sampler. Knowing the output x of the sampler for a given signature leads to linear information about the private key of the scheme. This paper includes several demonstrations of simple power analysis attacks targeting this sample x with various attacker strengths, all of them performed on the reference implementation on a ChipWhisperer Lite with STM32F3 target (ARM Cortex M4). We report being able to perform key recoveries with very low (to no) offline resources. As this reference implementation of HAWK is not claimed to be protected against side-channel attacks, the existence of such attacks is not surprising, but they still concretely warn about the use of this unprotected signature on physical devices. To finish, we propose an ad-hoc technique to lower down the leakage on the identified vulnerability points. These modifications prevent our attacks on our platform and come with essentially no cost in terms of performance. It could be seen as a temporary solution and encourages more analysis on proven side-channel protection of HAWK like masking.

HuFu is an unstructured lattice-based signature scheme proposed during the NIST PQC standardization process. In this work, we present a side-channel analysis of HuFu's reference implementation. We first exploit the multiplications involving its two main secret matrices, recovering approximately half of their entries through a non-profiled power analysis with a few hundred traces. Using these coefficients, we reduce the dimension of the underlying LWE problem, enabling full secret key recovery with calls to a small block-sized BKZ. To mitigate this attack, we propose a countermeasure that replaces sensitive computations involving a secret matrix with equivalent operations derived solely from public elements, eliminating approximately half of the identified leakage and rendering the attack unfeasible. Finally, we perform a non-profiled power analysis targeting HuFu's Gaussian sampling procedure, recovering around 75\% of the remaining secret matrix's entries in a few hundred traces. While full key recovery remains computationally intensive, we demonstrate that partial knowledge of the secret significantly improves the efficiency of signature forgery.

The use of MPC-in-the-Head (MPCitH)-based zero-knowledge proofs of knowledge (ZKPoK) to prove knowledge of a preimage of a one-way function (OWF) is a popular approach towards constructing efficient post-quantum digital signatures. Starting with the Picnic signature scheme, many optimized MPCitH signatures using a variety of (candidate) OWFs have been proposed. Recently, Baum et al. (CRYPTO 2023) showed a fundamental improvement to MPCitH, called VOLE-in-the-Head (VOLEitH), which can generically reduce the signature size by at least a factor of two without decreasing computational performance or introducing new assumptions. Based on this, they designed the FAEST signature which uses AES as the underlying OWF. However, in comparison to MPCitH, the behavior of VOLEitH when using other OWFs is still unexplored. In this work, we improve a crucial building block of the VOLEitH and MPCitH approaches, the so-called all-but-one vector commitment, thus decreasing the signature size of VOLEitH and MPCitH signature schemes. Moreover, by introducing a small Proof of Work into the signing procedure, we can improve the parameters of VOLEitH (further decreasing signature size) without compromising the computational performance of the scheme. Based on these optimizations, we propose three VOLEitH signature schemes FAESTER, KuMQuat, and MandaRain based on AES, MQ, and Rain, respectively. We carefully explore the parameter space for these schemes and implement each, showcasing their performance with benchmarks. Our experiments show that these three signature schemes outperform MPCitH-based competitors that use comparable OWFs, in terms of both signature size and signing/verification time.

This paper addresses the critical challenges in designing cryptographic algorithms that achieve both high performance and cross-platform efficiency on ARM and x86 architectures, catering to the demanding requirements of next-generation communication systems, such as 6G and GPU/NPU interconnections. We propose HiAE, a high-throughput authenticated encryption algorithm optimized for performance exceeding 100 Gbps and designed to meet the stringent security requirements of future communication networks. HiAE leverages the stream cipher structure, integrating the AES round function for non-linear diffusion. Our design achieves exceptional efficiency, with benchmark results from software implementations across various platforms showing over 340 Gbps on x86 processors and 180 Gbps on ARM devices in AEAD mode, making it the fastest AEAD solution on ARM chips and setting a new performance record on the latest x86 processors.

In order to compute a multiple of a point on an elliptic curve in Weierstrass form one can use formulas in only one of the two coordinates of the points. These $x$-only formulas can be seen as an arithmetic on the Kummer line associated to the curve. In this paper, we look at models of Kummer lines, and define an intrinsic notion of isomorphisms of Kummer lines. This allows us to give conversion formulas between Kummer models in a unified manner. When there is one rational point $T$ of $2$-torsion on the curve, we also use Mumford's theory of theta groups to show that there are two type of models: the “symmetric” ones with respect to $T$ and the “anti-symmetric“ ones. We show how this recovers the Montgomery model and various variants of the theta model. We also classify when curves admit these different models via Galois representations and modular curves. When an elliptic curve is viewed inside a $2$-isogeny volcano, we give a criteria to say if it has a given Kummer model based solely on its position in the volcano. We also give applications to the ECM factorization algorithm.

We revisit the privacy and security analyses of FIDO2, a widely deployed standard for passwordless authentication on the Web. We discuss previous works and conclude that each of them has at least one of the following limitations: (i) impractical trusted setup assumptions, (ii) security models that are inadequate in light of state of the art of practical attacks, (iii) not analyzing FIDO2 as a whole, especially for its privacy guarantees. Our work addresses these gaps and proposes revised security models for privacy and authentication. Equipped with our new models, we analyze FIDO2 modularly and focus on its component protocols, WebAuthn and CTAP2, clarifying their exact security guarantees. In particular, our results, for the first time, establish privacy guarantees for FIDO2 as a whole. Furthermore, we suggest minor modifications that can help FIDO2 provably meet stronger privacy and authentication definitions and withstand known and novel attacks.

This paper presents a security analysis of the South Korean Format-Preserving Encryption (FPE) standards FEA-1 and FEA-2. In 2023, Chauhan \textit{et al.} presented the first third-party analysis of FEA-1 and FEA-2 against the square attack. The authors proposed new distinguishing attacks covering up to three rounds of FEA-1 and five rounds of FEA-2, with a data complexity of $2^8$ plaintexts. Additionally, using these distinguishers, they presented key recovery attacks for four rounds of FEA-1 and six rounds of FEA-2, for 192-bit and 256-bit key sizes. The complexities of both the four-round FEA-1 and six-round FEA-2 key recovery attacks are $2^{137.6}$. \\ In this work, we successfully extend the number of rounds attacked for both FEA-1 and FEA-2, using the square attack technique. Specifically, we present a four-round distinguishing attack against FEA-1 and six-round distinguishing attack against FEA-2. The data complexities of these distinguishers are $2^{64}$ plaintexts. Furthermore, we apply these distinguishers to perform key recovery attacks on five rounds of FEA-1 and seven rounds of FEA-2, targeting the 256-bit key size. The time complexities of the presented key recovery attacks are $2^{193.6}$.

Systems such as file backup services often use content-defined chunking (CDC) algorithms, especially those based on rolling hash techniques, to split files into chunks in a way that allows for data deduplication. These chunking algorithms often depend on per-user parameters in an attempt to avoid leaking information about the data being stored. We present attacks to extract these chunking parameters and discuss protocol-agnostic attacks and loss of security once the parameters are breached (including when these parameters are not setup at all, which is often available as an option). Our parameter-extraction attacks themselves are protocol-specific but their ideas are generalizable to many potential CDC schemes.

The current landscape of system-on-chips (SoCs) security verification faces challenges due to manual, labor-intensive, and inflexible methodologies. These issues limit the scalability and effectiveness of security protocols, making bug detection at the Register-Transfer Level (RTL) difficult. This paper proposes a new framework named BugWhisperer that utilizes a specialized, fine-tuned Large Language Model (LLM) to address these challenges. By enhancing the LLM's hardware security knowledge and leveraging its capabilities for text inference and knowledge transfer, this approach automates and improves the adaptability and reusability of the verification process. We introduce an open-source, fine-tuned LLM specifically designed for detecting security vulnerabilities in SoC designs. Our findings demonstrate that this tailored LLM effectively enhances the efficiency and flexibility of the security verification process. Additionally, we introduce a comprehensive hardware vulnerability database that supports this work and will further assist the research community in enhancing the security verification process.

Ethereum is a decentralized and permissionless network offering several attractive features. However, block proposers in Ethereum can exploit the order of transactions to extract value. This phenomenon, known as $maximal$ $extractable$ $value$ (MEV), not only disrupts the optimal functioning of different protocols but also undermines the stability of the underlying consensus mechanism. Furthermore, current block production architecture allows transaction censorship that compromises credible neutrality, a fundamental principle of Ethereum’s design philosophy. In this work, we present a novel $mempool$ $encryption$ scheme to alleviate the censorship and MEV problem by separating transaction inclusion and execution, keeping transactions encrypted before execution. We formulate the notion of $multiparty$ $delay$ $encryption$ (MDE) and construct a practical MDE scheme based on time-lock puzzles. Our method excels in scalability (in terms of transaction decryption), efficiency (minimizing communication and storage overhead), and security (with minimal trust assumptions). To demonstrate the effectiveness of our MDE scheme, we have implemented it on a local Ethereum testnet and prove its security under the presence of only one honest attestation aggregator per Ethereum slot.

We consider 3 related cryptographic primitives, private information retrieval (PIR) protocols, conditional disclosure of secrets (CDS) protocols, and secret-sharing schemes; these primitives have many applications in cryptography. We study these primitives requiring information-theoretic security. The complexity of the three primitives has been dramatically improved in the last few years and they are closely related, i.e., the 2-server PIR protocol of Dvir and Gopi (J. ACM 2016) was transformed to construct the CDS protocols of Liu, Vaikuntanathan, and Wee (CRYPTO 2017, Eurocrypt 2018) and these CDS protocols are the main ingredient in the construction of the best-known secret-sharing schemes. To date, the message size required in PIR and CDS protocols and the share size required in secret-sharing schemes are not understood and there are big gaps between their upper bounds and lower bounds. The goal of this paper is to try to better understand the upper bounds by simplifying current constructions and improving their complexity. We obtain the following two independent results: - We simplify, abstract, and generalize the 2-server PIR protocol of Dvir and Gopi (J. ACM 2016), the recent multi-server PIR protocol of Ghasemi, Kopparty, and Sudan (STOC 2025), and the 2-server and multi-server CDS protocols of Liu et al. (CRYPTO 2017, Eurocrypt 2018) and Beimel, Farr`as, and Lasri (TCC 2023). In particular, we present one PIR protocol generalizing both the 2- server and multi-server PIR protocols. This is done by considering a new variant of matching vectors and by using a general share conversion. In addition to simplifying previous protocols, our 2-server protocols can use matching vectors over any $m$ that is the product of two distinct primes. Our construction does not improve the communication complexity of PIR and CDS protocols; however, construction of better matching vectors over $\textit{any}$ $m$ that is the product of two distinct primes will improve the communication complexity of 2-server PIR and CDS protocols. - In many applications of secret-sharing schemes it is important that the scheme is linear, e.g., by using the fact that parties can locally add shares of two secrets and obtain shares of the sum of the secrets. We provide a construction of linear secret-sharing schemes for $n$-party access structures with improved share size of $2^{0.7563n}$. Previously, the best share size for linear secret-sharing schemes was $2^{0.7576n}$ and it is known that for most $n$-party access structures the shares' size is at least $2^{0.5n}$. This result is achieved by a reduction to unbalanced CDS protocols (compared to balanced CDS protocols in previous constructions).

CHide is one of the most prominent e-voting protocols, which, while combining security and efficiency, suffers from having very long encrypted credentials. In this paper, starting from CHide, we propose a new protocol, based on multiparty Class Group Encryption (CGE) instead of discrete logarithm cryptography over known order groups, achieving a computational complexity of $O(nr)$, for $n$ votes and $r$ voters, and using a single MixNet. The homomorphic properties of CGE allow for more compact credentials while maintaining the same level of security at the cost of a small slowdown in efficiency.

We show that using a polynomial representation of prime field elements (PMNS) can be relevant for real-world cryptographic applications even in terms of performance. More specifically, we consider elliptic curves for cryptography when pseudo-Mersenne primes cannot be used to define the base field (e.g. Brainpool standardized curves, JubJub curves in the zkSNARK context, pairing-friendly curves). All these primitives make massive use of the Montgomery reduction algorithm and well-known libraries such as GMP or OpenSSL for base field arithmetic. We show how this arithmetic can be replaced by a polynomial representation of the number that can be easily parallelized, avoids carry propagation, and allows randomization process. We provide good PMNS basis in the cryptographic context mentioned above, together with a C-implementation that is competitive with GMP and OpenSSL for performing basic operations in the base fields considered. We also integrate this arithmetic into the Rust reference implementation of elliptic curve scalar multiplication for Zero-knowledge applications, and achieve better practical performances for such protocols. This shows that PMNS is an attractive alternative for the base field arithmetic layer in cryptographic primitives using elliptic curves or pairings.

The ETSI Technical Specification 104 015 proposes a framework to build Key Encapsulation Mechanisms (KEMs) with access policies and attributes, in the Ciphertext-Policy Attribute-Based Encryption (CP-ABE) vein. Several security guarantees and functionalities are claimed, such as pre-quantum and post-quantum hybridization to achieve security against Chosen-Ciphertext Attacks (CCA), anonymity, and traceability. In this paper, we present a formal security analysis of a more generic construction, with application to the specific Covercrypt scheme, based on the pre-quantum ECDH and the post-quantum ML-KEM KEMs. We additionally provide an open-source library that implements the ETSI standard, in Rust, with high effiency.

Recent advances in Vector Oblivious Linear Evaluation (VOLE) protocols have enabled constant-round, fast, and scalable (designated-verifier) zero-knowledge proofs, significantly reducing prover computational cost. Existing protocols, such as QuickSilver [CCS’21] and LPZKv2 [CCS’22], achieve efficiency with prover costs of 4 multiplications in the extension field per AND gate for Boolean circuits, with one multiplication requiring a O(κ log κ)-bit operation where κ = 128 is the security parameter and 3-4 field multiplications per multiplication gate for arithmetic circuits over a large field. We introduce JesseQ, a suite of two VOLE-based protocols: JQv1 and JQv2, which advance state of the art. JQv1 requires only 2 scalar multiplications in an extension field per AND gate for Boolean circuits, with one scalar needing a O(κ)- bit operation, and 2 field multiplications per multiplication gate for arithmetic circuits over a large field. In terms of communication costs, JQv1 needs just 1 field element per gate. JQv2 further reduces communication costs by half at the cost of doubling the prover’s computation. Experiments show that, compared to the current state of the art, both JQv1 and JQv2 achieve at least 3.9× improvement in the online phase for Boolean circuits. For large field circuits, JQv1 has a similar performance, while JQv2 offers a 1.3× improvement. Additionally, both JQv1 and JQv2 maintain the same communication cost as the current state of the art. Notably, on the cheapest AWS instances, JQv1 can prove 9.2 trillion AND gates (or 5.8 trillion multiplication gates over a 61-bit field) for just one US dollar. JesseQ excels in applications like inner products, matrix multiplication, and lattice problems, delivering 40%- 200% performance improvements compared to QuickSilver. Additionally, JesseQ integrates seamlessly with the sublinear Batchman framework [CCS’23], enabling further efficiency gains for batched disjunctive statements.

The use of small fields has come to typify the design of modern, efficient SNARKs. In recent work, Diamond and Posen (EUROCRYPT '25) break a key trace-length barrier, by treating multilinear polynomials even over tiny fields—fields with fewer elements than the polynomial has coefficients. In this work, we make that advance applicable globally, by generically reducing the problem of tiny-field commitment to that of large-field commitment. We introduce a sumcheck-based technique—which we call "ring-switching"—which, on input a multilinear polynomial commitment scheme over a large extension field, yields a further scheme over that field's ground field. The resulting tiny-field scheme, like Diamond and Posen's, lacks "embedding overhead", in the sense that its commitment cost is identical to that of the large-field scheme on each input size (measured in bits). Its evaluation protocol adds to the cost of the underlying large-field scheme's just a concretely small, additive polylogarithmic overhead. Instantiating our compiler on the BaseFold (CRYPTO '24) large-field multilinear polynomial commitment scheme—or more precisely, on a characteristic-2 adaptation of that scheme, which we develop at length—we obtain an extremely efficient scheme for multilinears over tiny binary fields. Our scheme outperforms Diamond–Posen and represents a new state-of-the-art.

Postal voting is a frequently used alternative to on-site voting. Traditionally, its security relies on organizational measures, and voters have to trust many entities. In the recent years, several schemes have been proposed to add verifiability properties to postal voting, while preserving vote privacy. Postal voting comes with specific constraints. We conduct a systematic analysis of this setting and we identify a list of generic attacks, highlighting that some attacks seem unavoidable. This study is applied to existing systems of the literature. We then propose Vote&Check, a postal voting protocol which provides a high level of security, with a reduced number of authorities. Furthermore, it requires only basic cryptographic primitives, namely hash functions and signatures. The security properties are proven in a symbolic model, with the help of the ProVerif tool.

Over two decades since their introduction in 2005, all major verifiable pairing delegation protocols for public inputs have been designed to ensure information-theoretic security. However, we note that a delegation protocol involving only ephemeral secret keys in the public view can achieve everlasting security, provided the server is unable to produce a pairing forgery within the protocol’s execution time. Thus, computationally bounding the adversary’s capabilities during the protocol’s execution, rather than across its entire lifespan, may be more reasonable, especially when the goal is to achieve significant efficiency gains for the delegating party. This consideration is particularly relevant given the continuously evolving computational costs associated with pairing computations and their ancillary blocks, which creates an ever-changing landscape for what constitutes efficiency in pairing delegation protocols. With the goal of fulfilling both efficiency and everlasting security, we present AmorE, a protocol equipped with an adjustable security and efficiency parameter for sequential pairing delegation, which achieves state-of-the-art amortized efficiency in terms of the number of pairing computations. For example, delegating batches of 10 pairings on the BLS48-575 elliptic curve via our protocol costs to the client, on average, less than a single scalar multiplication in G2 per delegated pairing, while still ensuring at least 40 bits of statistical security.

Power side-channel (PSC) vulnerabilities present formidable challenges to the security of ubiquitous microelectronic devices in mission-critical infrastructure. Existing side-channel assessment techniques mostly focus on post-silicon stages by analyzing power profiles of fabricated devices, suffering from low flexibility and prohibitively high cost while deploying security countermeasures. While pre-silicon PSC assessments offer flexibility and low cost, the true nature of the power signatures cannot be fully captured through RTL or gate-level design. Although physical design-level analysis provides precise power traces, collecting data is time and resource-consuming at the layout level. To address this challenge, we propose, for the first time, a fast and efficient physical design-level PSC assessment framework using a graph neural network (GNN). This framework predicts dynamic power traces for new layouts, using them to assess physical design security through metrics evaluation. Our experiments on AES-GF layout implementations achieve a tremendous 133 times speedup compared to conventional simulation-based flow without sacrificing substantial accuracy.

Practical signature-based witness encryption (SWE) schemes recently emerged as a viable alternative to instantiate timed-release cryptography in the honest majority setting. In particular, assuming threshold trust in a set of parties that release signatures at a specified time, one can ``encrypt to the future'' using an SWE scheme. Applications of SWE schemes include voting, auctions, distributed randomness beacons, and more. However, the lack of homomorphism in existing SWE schemes reduces efficiency and hinders deployment. In this work, we introduce the notion of homomorphic SWE (HSWE) to improve the practicality of timed-release encryption schemes. We show one can build HSWE using a pair of encryption and signature schemes where the uniqueness of the signature is required when the encryption scheme relies on injective one-way functions. We then build three HSWE schemes in various settings using BLS, RSA, and Rabin signatures and show how to achieve a privacy-preserving variant that only allows extracting the homomorphically aggregated result while keeping the individual plaintexts confidential

SNOVA is one of the submissions in the NIST Round 1 Additional Signature of the Post-Quantum Signature Competition. SNOVA is a UOV variant that uses the noncommutative-ring technique to educe the size of the public key. SNOVA's public key size and signature size are well-balanced and have good performance. Recently, Beullens proposed a forgery attack against SNOVA, pointing out that the parameters of SNOVA can be attacked. Beullens also argued that with some slight adjustments his attacks can be prevented. In this note, we explain Beullens' forgery attack and show that the attack can be invalid by two different approaches. Finally, we show that these two approaches do not increase the sizes of the public keys or signatures and the current parameters satisfy the security requirement of NIST.

Encrypted search schemes have been proposed to address growing privacy concerns. However, several leakage-abuse attacks have highlighted some security vulnerabilities. Recent attacks assumed an attacker's knowledge containing data "similar" to the indexed data. However, this vague assumption is barely discussed in literature: how likely is it for an attacker to obtain a "similar enough" data? Our paper provides novel statistical tools usable on any attack in this setting to analyze its sensitivity to data similarity. First, we introduce a mathematical model based on statistical estimators to analytically understand the attackers' knowledge and the notion of similarity. Second, we conceive statistical tools to model the influence of the similarity on the attack accuracy. We apply our tools on three existing attacks to answer questions such as: is similarity the only factor influencing accuracy of a given attack? Third, we show that the enforcement of a maximum index size can make the ``similar-data'' assumption harder to satisfy. In particular, we propose a statistical method to estimate an appropriate maximum size for a given attack and dataset. For the best known attack on the Enron dataset, a maximum index size of 200 guarantees (with high probability) the attack accuracy to be below 5%.

SNARKs are frequently used to prove encryption, yet the circuit size often becomes large due to the intricate operations inherent in encryption. It entails considerable computational overhead for a prover and can also lead to an increase in the size of the public parameters (e.g., evaluation key). We propose an encryption-friendly SNARK framework, $\textsf{Tangram}$, which allows anyone to construct a system by using their desired encryption and proof system. Our approach revises existing encryption schemes to produce Pedersen-like ciphertext, including identity-based, hierarchical identity-based, and attribute-based encryption. Afterward, to prove the knowledge of the encryption, we utilize a modular manner of commit-and-prove SNARKs, which uses commitment as a `bridge'. With our framework, one can prove encryption significantly faster than proving the whole encryption within the circuit. We implement various $\textsf{Tangram}$ gadgets and evaluate their performance. Our results show 12x - 3500x times better performance than encryption-in-the-circuit.

Blockchain advancements, currency digitalization, and declining cash usage have fueled global interest in Central Bank Digital Currencies (CBDCs). The BIS states that the hybrid model, where central banks authorize intermediaries to manage distribution, is more suitable than the direct model. However, designing a CBDC for practical implementation requires careful consideration. First, the public blockchain raises privacy concerns due to transparency. While zk-SNARKs can be a solution, they can introduce significant proof generation overhead for large-scale transactions. Second, intermediaries that provide user-facing services on behalf of the central bank commonly performs Proof of Liabilities on customers' static liabilities. However, in real-world scenarios where user liabilities can arbitrarily increase or decrease, the static nature poses such as window attacks. In this paper, we propose a new smart contract-based privacy-preserving CBDC framework based on zk-SNARKs, called $\textbf{Aegis}$. our framework introduces a transaction batching technique to enhance scalability and defines a new dynamic PoL which is near-real time. We formally define the security models for our system and provide rigorous security proofs to demonstrate its robustness. To evaluate the system’s performance, we instantiate our proposed framework and measure its efficiency. The result indicates that, the end-to-end process, including proof generation for 512 transactions, takes approximately 2.8 seconds, with a gas consumption of 74,726 per user.

Homomorphically encrypted matrix operations are extensively used in various privacy-preserving applications. Consequently, reducing the cost of encrypted matrix operations is a crucial topic on which numerous studies have been conducted. In this paper, we introduce a novel matrix encoding method, named bicyclic encoding, under which we propose two new algorithms BMM-I and BMM-II for encrypted matrix multiplication. BMM-II outperforms the stat-of-the-art algorithms in theory, while BMM-I, combined with the segmented strategy, performs well in practice, particularly for matrices with high dimensions. Another noteworthy advantage of bicyclic encoding is that it allows for transposing an encrypted matrix entirely free. A comprehensive experimental study based on our proof-of-concept implementation shows that each algorithm introduced in this paper has specific scenarios outperforming existing algorithms, achieving speedups ranging from 2x to 38x.

Digital signatures underpin identity, authenticity, and trust in modern computer systems. Cryptography research has shown that it is possible to prove possession of a valid message and signature for some public key, without revealing the message or signature. These proofs of possession work only for specially-designed signature schemes. Though these proofs of possession have many useful applications to improving security, privacy, and anonymity, they are not currently usable for widely deployed, legacy signature schemes such as RSA, ECDSA, and Ed25519. Unlocking practical proofs of possession for these legacy signature schemes requires closing a huge efficiency gap. This work brings proofs of possession for legacy signature schemes very close to practicality. Our design strategy is to encode the signature's verification algorithm as a rank-one constraint system (R1CS), then use a zkSNARK to prove knowledge of a solution. To do this efficiently we (1) design and analyze a new zkSNARK called Dorian that supports randomized computations, (2) introduce several new techniques for encoding hashes, elliptic curve operations, and modular arithmetic, (3) give a new approach that allows performing the most expensive parts of ECDSA and Ed25519 verifications outside R1CS, and (4) generate a novel elliptic curve that allows expressing Ed25519 curve operations very efficiently. Our techniques reduce R1CS sizes by up to 200$\times$ and prover times by 3-22$\times$. We can generate a 240-byte proof of possession of an RSA signature over a message the size of a typical TLS certificate (two kilobytes) in only three seconds.

Shadow is a family of lightweight block ciphers introduced by Guo, Li, and Liu in 2021, with Shadow-32 having a 32-bit block size and a 64-bit key, and Shadow-64 having a 64-bit block size and a 128-bit key. Both variants use a generalized Feistel network with four branches, incorporating the AND-Rotation-XOR operation similar to the Simon family for their bridging function. This paper reveals that the security claims of the Shadow family are not as strong as suggested. We present a key recovery attack that can retrieve the sequence of round keys used for encryption with only two known plaintext/ciphertext pairs, requiring time and memory complexity of $2^{43.23}$ encryptions and $2^{21.62}$ blocks of memory for Shadow-32, and complexity of $2^{81.32}$ encryptions and $2^{40.66}$ blocks of memory for Shadow-64. Notably, this attack is independent of the number of rounds and the bridging function employed. Furthermore, we critically evaluate one of the recent cryptanalysis on Shadow ciphers and identify significant flaws in the proposed key recovery attacks. In particular, we demonstrate that the distinguisher used in impossible differential attacks by Liu et al. is ineffective for key recovery, despite their higher claimed complexities compared to ours.

Tremendous efforts have been made to improve the efficiency of secure Multi-Party Computation (MPC), which allows n ≥ 2 parties to jointly evaluate a target function without leaking their own private inputs. It has been confirmed by previous research that Three-Party Computation (3PC) and outsourcing computations to GPUs can lead to huge performance improvement of MPC in computationally intensive tasks such as Privacy-Preserving Machine Learning (PPML). A natural question to ask is whether super-linear performance gain is possible for a linear increase in resources. In this paper, we give an affirmative answer to this question. We propose Force, an extremely efficient Four-Party Computation (4PC) system for PPML. To the best of our knowledge, each party in Force enjoys the least number of local computations, smallest graphic memory consumption and lowest data exchanges between parties. This is achieved by introducing a new sharing type X-share along with MPC protocols in privacy-preserving training and inference that are semi-honest secure in the honest-majority setting. By comparing the results with state-of-the-art research, we showcase that Force is sound and extremely efficient, as it can improve the PPML performance by a factor of 2 to 38 compared with other latest GPU-based semi-honest secure systems, such as Piranha (including SecureML, Falcon, FantasticFour), CryptGPU and CrypTen.

In this paper we characterize all $2n$-bit-to-$n$-bit Pseudorandom Functions (PRFs) constructed with the minimum number of calls to $n$-bit-to-$n$-bit PRFs and arbitrary number of linear functions. First, we show that all two-round constructions are either classically insecure, or vulnerable to quantum period-finding attacks. Second, we categorize three-round constructions depending on their vulnerability to these types of attacks. This allows us to identify classes of constructions that could be proven secure. We then proceed to show the security of the following three candidates against any quantum distinguisher that asks at most $ 2^{n/4} $ (possibly superposition) queries \[ \begin{array}{rcl} \mathsf{TNT}(x_1,x_2) &:=& f_3(x_2 \oplus f_2(x_2 \oplus f_1(x_1)))\\ \mathsf{LRQ}(x_1,x_2) &:=& f_2(x_2) \oplus f_3(x_2 \oplus f_1(x_1))\\ \mathsf{LRWQ}(x_1,x_2) &:=& f_3( f_1(x_1) \oplus f_2(x_2)). \end{array} \] Note that the first construction is a classically secure tweakable block cipher due to Bao et al., and the third construction is shown to be quantum secure tweakable block cipher by Hosoyamada and Iwata with similar query limits. Of note is our proof framework, an adaptation of Chung et al.'s rigorous formulation of Zhandry's compressed oracle technique in indistinguishability setup, which could be of independent interests. This framework gives very compact and mostly classical looking proofs as compared to Hosoyamada and Iwata interpretation of Zhandry's compressed oracle.

The Classical Bloom Filter (CBF) is a class of Probabilistic Data Structures (PDS) for handling Approximate Query Membership (AMQ). The Learned Bloom Filter (LBF) is a recently proposed class of PDS that combines the Classical Bloom Filter with a Learning Model while preserving the Bloom Filter's one-sided error guarantees. Bloom Filters have been used in settings where inputs are sensitive and need to be private in the presence of an adversary with access to the Bloom Filter through an API or in the presence of an adversary who has access to the internal state of the Bloom Filter. This paper conducts a rigorous differential privacy-based analysis for the Bloom Filter. We propose constructions that satisfy differential privacy and asymmetric differential privacy. This is also the first work that analyses and addresses the privacy of the Learned Bloom Filter under any rigorous model, which is an open problem.

The Fiat-Shamir transformation underlies numerous non-interactive arguments, with variants that differ in important ways. This paper addresses a gap between variants analyzed by theoreticians and variants implemented (and deployed) by practitioners. Specifically, theoretical analyses typically assume parties have access to random oracles with sufficiently large input and output size, while cryptographic hash functions in practice have fixed input and output sizes (pushing practitioners towards other variants). In this paper we propose and analyze a variant of the Fiat-Shamir transformation that is based on an ideal permutation of fixed size. The transformation relies on the popular duplex sponge paradigm, and minimizes the number of calls to the permutation (given the amount of information to absorb and to squeeze). Our variant closely models deployed variants of the Fiat-Shamir transformation, and our analysis provides concrete security bounds that can be used to set security parameters in practice. We additionally contribute spongefish, an open-source Rust library implementing our Fiat-Shamir transformation. The library is interoperable across multiple cryptographic frameworks, and works with any choice of permutation. The library comes equipped with Keccak and Poseidon permutations, as well as several "codecs" for re-mapping prover and verifier messages to the permutation's domain.

As artificial intelligence (AI) becomes increasingly embedded in high-stakes applications such as healthcare, finance, and autonomous systems, ensuring the verifiability of AI computations without compromising sensitive data or proprietary models is crucial. Zero-knowledge machine learning (ZKML) leverages zero-knowledge proofs (ZKPs) to enable the verification of AI model outputs while preserving confidentiality. However, existing ZKML approaches require specialized cryptographic expertise, making them inaccessible to traditional AI developers. In this paper, we introduce ZKPyTorch, a compiler that seamlessly integrates ML frameworks like PyTorch with ZKP engines like Expander, simplifying the development of ZKML. ZKPyTorch automates the translation of ML operations into optimized ZKP circuits through three key components. First, a ZKP preprocessor converts models into structured computational graphs and injects necessary auxiliary information to facilitate proof generation. Second, a ZKP-friendly quantization module introduces an optimized quantization strategy that reduces computation bit-widths, enabling efficient ZKP execution within smaller finite fields such as M61. Third, a hierarchical ZKP circuit optimizer employs a multi-level optimization framework at model, operation, and circuit levels to improve proof generation efficiency. We demonstrate ZKPyTorch effectiveness through end-to-end case studies, successfully converting VGG-16 and Llama-3 models from PyTorch, a leading ML framework, into ZKP-compatible circuits recognizable by Expander, a state-of-the-art ZKP engine. Using Expander, we generate zero-knowledge proofs for these models, achieving proof generation for the VGG-16 model in 2.2 seconds per CIFAR-10 image for VGG-16 and 150 seconds per token for Llama-3 inference, improving the practical adoption of ZKML.

Rank-1 Constraint Systems (R1CS) and Plonk constraint systems are two commonly used circuit formats for zero-knowledge succinct non-interactive arguments of knowledge (zkSNARKs). We present Plonkify, a tool that converts a circuit in an R1CS arithmetization to Plonk, with support for both vanilla gates and custom gates. Our tool is able to convert an R1CS circuit with 229,847 constraints to a vanilla Plonk circuit with 855,296 constraints, or a jellyfish turbo Plonk circuit with 429,166 constraints, representing a $2.59\times$ and $1.9\times$ reduction in the number of constraints over the respective naïve conversions.

End-to-end encryption (E2EE) has become the gold standard for securing communications, bringing strong confidentiality and privacy guarantees to billions of users worldwide. However, the current push towards widespread integration of artificial intelligence (AI) models, including in E2EE systems, raises some serious security concerns. This work performs a critical examination of the (in)compatibility of AI models and E2EE applications. We explore this on two fronts: (1) the integration of AI assistants within E2EE applications, and (2) the use of E2EE data for training AI models. We analyze the potential security implications of each, and identify conflicts with the security guarantees of E2EE. Then, we analyze legal implications of integrating AI models in E2EE applications, given how AI integration can undermine the confidentiality that E2EE promises. Finally, we offer a list of detailed recommendations based on our technical and legal analyses, including: technical design choices that must be prioritized to uphold E2EE security; how service providers must accurately represent E2EE security; and best practices for the default behavior of AI features and for requesting user consent. We hope this paper catalyzes an informed conversation on the tensions that arise between the brisk deployment of AI and the security offered by E2EE, and guides the responsible development of new AI features.

We construct a novel code-based blind signature scheme, us- ing the Matrix Equivalence Digital Signature (MEDS) group action. The scheme is built using similar ideas to the Schnorr blind signature scheme and CSI-Otter, but uses additional public key and commitment informa- tion to overcome the difficulties that the MEDS group action faces: lack of module structure (present in Schnorr), lack of a quadratic twist (present in CSI-Otter), and non-commutativity of the acting group. We address security concerns related to public key validation, and prove the security of our protocol in the random oracle model, using the security framework of Kastner, Loss, and Xu, under a variant of the Inverse Matrix Code Equivalence problem and a mild heuristic assumption.

We construct a pairing-based polynomial commitment scheme for multilinear polynomials of size $n$ where constructing an opening proof requires $O(n)$ field operations, and $2n+O(\sqrt n)$ scalar multiplications. Moreover, the opening proof consists of a constant number of field elements. This is a significant improvement over previous works which would require either 1. $O(n\log n)$ field operations; or 2. $O(\log n)$ size opening proof. The main technical component is a new method of verifiably folding a witness via univariate polynomial division. As opposed to previous methods, the proof size and prover time remain constant *regardless of the folding factor*.

Registration-based encryption (RBE) is a recently developed alternative to identity-based encryption, that mitigates the well-known key-escrow problem by letting each user sample its own key pair. In RBE, the key authority is substituted by a key curator, a completely transparent entity whose only job is to reliably aggregate users' keys. However, one limitation of all known RBE scheme is that they all rely on one-time trusted setup, that must be computed honestly. In this work, we ask whether this limitation is indeed inherent and we initiate the systematic study of RBE in the plain model, without any common reference string. We present the following main results: - (Definitions) We show that the standard security definition of RBE is unachievable without a trusted setup and we propose a slight weakening, where one honest user is required to be registered in the system. - (Constructions) We present constructions of RBE in the plain model, based on standard cryptographic assumptions. Along the way, we introduce the notions of non-interactive witness indistinguishable (NIWI) proofs secure against chosen statements attack and re-randomizable RBE, which may be of independent interest. A major limitation of our constructions, is that users must be updated upon every new registration. - (Lower Bounds) We show that this limitation is in some sense inherent. We prove that any RBE in the plain model that satisfies a certain structural requirement, which holds for all known RBE constructions, must update all but a vanishing fraction of the users, upon each new registration. This is in contrast with the standard RBE settings, where users receive a logarithmic amount of updates throughout the lifetime of the system.

Distinguishing Goppa codes or alternant codes from generic linear codes [FGO+11] has been shown to be a first step before being able to attack McEliece cryptosystem based on those codes [BMT24]. Whereas the distinguisher of [FGO+11] is only able to distinguish Goppa codes or alternant codes of rate very close to 1, in [CMT23a] a much more powerful (and more general) distinguisher was proposed. It is based on computing the Hilbert series $\{\mathrm{HF}(d),~d\in \mathbb{N}\}$ of a Pfaffian modeling. The distinguisher of [FGO+11] can be interpreted as computing $\mathrm{HF}(1)$. Computing $\mathrm{HF}(2)$ still gives a polynomial time distinguisher for alternant or Goppa codes and is apparently able to distinguish Goppa or alternant codes in a much broader regime of rates as the one of [FGO+11]. However, the scope of this distinguisher was unclear. We give here a formula for $\mathrm{HF}(2)$ corresponding to generic alternant codes when the field size $q$ satisfies $q \geq r$, where r is the degree of the alternant code. We also show that this expression for$\mathrm{HF}(2)$ provides a lower bound in general. The value of $\mathrm{HF}(2)$ corresponding to random linear codes is known and this yields a precise description of the new regime of rates that can be distinguished by this new method. This shows that the new distinguisher improves significantly upon the one given in [FGO+11].

This article presents an extension of the work performed by Liu, Baek and Susilo on extended withdrawable signatures to lattice-based constructions. We introduce a general construction, and provide security proofs for this proposal. As instantiations, we provide concrete construction for extended withdrawable signature schemes based on Dilithium and HAETAE.

Group actions have emerged as a powerful framework in post-quantum cryptography, serving as the foundation for various cryptographic primitives. The Lattice Isomorphism Problem (LIP) has recently gained attention as a promising hardness assumption for designing quantum-resistant protocols. Its formulation as a group action has opened the door to new cryptographic applications, including a commitment scheme and a linkable ring signature. In this work, we analyze the security properties of the LIP group action and present new findings. Specifically, we demonstrate that it fails to satisfy the weak unpredictability and weak pseudorandomness properties when the adversary has access to as few as three and two instances with the same secret, respectively. This significantly improves upon prior analysis by Budroni et al. (PQCrypto 2024). As a direct consequence of our findings, we reveal a vulnerability in the linkable ring signature scheme proposed by Khuc et al. (SPACE 2024), demonstrating that the hardness assumption underlying the linkable anonymity property does not hold.

We show that the anonymous authentication and key establishment scheme [IEEE TDSC, 20(4), 3535-3545, 2023] fails to keep user anonymity, not as claimed. We also suggest a method to fix it.

Federated Learning (FL) has recently emerged as one of the leading paradigms for collaborative machine learning, serving as a tool for model computation without a need to expose one’s privately stored data. However, despite its advantages, FL systems face severe challenges within its own security solutions that address both privacy and robustness of models. This paper focuses on vulnerabilities within the domain of FL security with emphasis on model-robustness. Identifying critical gaps in current defences, particularly against adaptive adversaries which modify their attack strategies after being disconnected and rejoin systems to continue attacks. To our knowledge, other surveys in this domain do not cover the concept of adaptive adversaries, this along with the significance of their impact serves as the main motivation for this work. Our contributions are fivefold: (1) we present a comprehensive overview of FL systems, presenting a complete summary of its fundamental building blocks, (2) an extensive overview of existing vulnerabilities that target FL systems in general, (3) highlight baseline attack vectors as well as state-of-the-art approaches to development of attack methods and defence mechanisms, (4) introduces a novel baseline method of attack leveraging reconnecting malicious clients, and (5) identifies future research directions to address and counter adaptive attacks. We demonstrate through experimental results that existing baseline secure aggregation rules used in other works for comparison such as Krum and Trimmed Mean are insufficient against those attacks. Further, works improving upon those algorithms do not address this concern either. Our findings serve as a basis for redefining FL security paradigms in the direction of adaptive adversaries.

Zero-knowledge range arguments are a fundamental cryptographic primitive that allows a prover to convince a verifier of the knowledge of a secret value lying within a predefined range. They have been utilized in diverse applications, such as confidential transactions, proofs of solvency and anonymous credentials. Range arguments with a transparent setup dispense with any trusted setup to eliminate security backdoor and enhance transparency. They are increasingly deployed in diverse decentralized applications on blockchains. One of the major concerns of practical deployment of range arguments on blockchains is the incurred gas cost and high computational overhead associated with blockchain miners. Hence, it is crucial to optimize the verification efficiency in range arguments to alleviate the deployment cost on blockchains and other decentralized platforms. In this paper, we present VeRange with several new zero-knowledge range arguments in the discrete logarithm setting, requiring only $c \sqrt{N/\log N}$ group exponentiations for verification, where $N$ is the number of bits to represent a range and $c$ is a small constant, making them concretely efficient for blockchain deployment with a very low gas cost. Furthermore, VeRange is aggregable, allowing a prover to simultaneously prove $T$ range arguments in a single argument, requiring only $O(\sqrt{TN/\log (TN)}) + T$ group exponentiations for verification. We deployed {\tt VeRange} on Ethereum and measured the empirical gas cost, achieving the fastest verification runtime and the lowest gas cost among the discrete-logarithm-based range arguments in practice.

Blockchain technology and smart contracts have revolutionized digital transactions by enabling trustless and decentralized exchanges of value. However, the inherent transparency and immutability of blockchains pose significant privacy challenges. On-chain data, while pseudonymous, is publicly visible and permanently recorded, potentially leading to the inadvertent disclosure of sensitive information. This issue is particularly pronounced in smart contract applications, where contract details are accessible to all network participants, risking the exposure of identities and transactional details. To address these privacy concerns, there is a pressing need for privacy-preserving mechanisms in smart contracts. To showcase this need even further, in our paper we bring forward advanced use-cases in economics which only smart contracts equipped with privacy mechanisms can realize, and show how fully-homomorphic encryption (FHE) as a privacy enhancing technology (PET) in smart contracts, operating on a public blockchain, can make possible the implementation of these use-cases. Furthermore, we perform a comprehensive systematization of FHE-based approaches in smart contracts, examining their potential to maintain the confidentiality of sensitive information while retaining the benefits of smart contracts, such as automation, decentralization, and security. After we evaluate these existing FHE solutions in the context of the use-cases we consider, we identify open problems, and suggest future research directions to enhance privacy in blockchain smart contracts.

Deimos Cipher is a symmetric encryption algorithm designed to achieve high entropy, strong diffusion, and computational efficiency. It integrates HKDF with BLAKE2b for key expansion, ensuring secure key derivation from user-supplied passwords. The encryption process employs XChaCha20, a high-speed stream cipher, to provide strong security and resistance against nonce reuse attacks. To guarantee data integrity and authentication, HMAC-SHA256 is used, preventing unauthorized modifications. Security evaluations demonstrate that Deimos Cipher exhibits superior randomness, achieving 6.24 bits per byte entropy for short plaintexts and 7.9998 bits per byte for long plaintexts, surpassing industry standards like AES and ChaCha20. Avalanche Effect analysis confirms optimal diffusion, with 50.18% average bit change, ensuring high resistance to differential cryptanalysis. Additionally, key sensitivity tests reveal 50.54% ciphertext change for minimal key variations, making brute-force and key-recovery attacks impractical. With its combination of a robust key expansion mechanism, stream cipher encryption, and cryptographic authentication, Deimos Cipher offers a secure and efficient encryption scheme suitable for secure messaging, cloud data protection, and high-security environments. This paper presents the algorithm’s design, security analysis, and benchmarking against established cryptographic standards.

Datasets of side-channel leakage measurements are widely used in research to develop and benchmark side-channel attack and evaluation methodologies. Compared to using custom and/or one-off datasets, widely-used and publicly available datasets improve research reproducibility and comparability. Further, performing high-quality measurements requires specific equipment and skills, while also taking a significant amount of time. Therefore, using publicly available datasets lowers the barriers to entry into side-channel research. This paper introduces the SMAesH dataset. SMAesH is an optimized masked hardware implementation of the AES with a provably secure arbitrary-order masking scheme. The SMAesH dataset contains power traces of the first-order protected version of SMAesH acquired on two FPGAs from different generations, along with key, plaintext and masking randomness. A part of the dataset use uniformly random key and plaintext to enable leakage profiling, while another part uses a fixed key (still with uniformly random plaintext) to enable attack validation or leakage assessment in a fixed-versus-random setting. We document the experimental setup used to acquire the dataset and also discuss particular methods employed to maximize the information content in the leakage traces, such as power supply selection, fine-grained trace alignment and resolution optimization. We perfom an in-depth leakage analysis for the two targets. Finally, we briefly discuss the known attacks against the dataset.

Automated market makers (AMMs) are a prime example of Web 3.0 applications. Their popularity and high trading activity led to serious scalability issues in terms of throughput and state size. In this paper, we address these challenges by utilizing a new sidechain architecture, building a system called ammBoost. ammBoost reduces the amount of on-chain transactions, boosts throughput, and supports blockchain pruning. We devise several techniques to enable layer 2 processing for AMMs, including a functionality-split and layer 2 traffic summarization paradigm, an epoch-based deposit mechanism, and pool snapshot-based and delayed token-payout trading. We also build a proof-of-concept for a Uniswap-inspired use case to empirically evaluate performance. Our experiments show that ammBoost decreases the gas cost by 96.05% and the chain growth by at least 93.42%, and that it can support up to 500x of the daily traffic volume of Uniswap. We also compare ammBoost to an Optimism-inspired solution showing a 99.94% reduction in transaction finality.

The integration of AI agents with Web3 ecosystems harnesses their complementary potential for autonomy and openness, yet also introduces underexplored security risks, as these agents dynamically interact with financial protocols and immutable smart contracts. This paper investigates the vulnerabilities of AI agents within blockchain-based financial ecosystems when exposed to adversarial threats in real-world scenarios. We introduce the concept of context manipulation -- a comprehensive attack vector that exploits unprotected context surfaces, including input channels, memory modules, and external data feeds. Through empirical analysis of ElizaOS, a decentralized AI agent framework for automated Web3 operations, we demonstrate how adversaries can manipulate context by injecting malicious instructions into prompts or historical interaction records, leading to unintended asset transfers and protocol violations which could be financially devastating. Our findings indicate that prompt-based defenses are insufficient, as malicious inputs can corrupt an agent's stored context, creating cascading vulnerabilities across interactions and platforms. This research highlights the urgent need to develop AI agents that are both secure and fiduciarily responsible.

We introduce deniable secret sharing (DSS), which, analogously to deniable encryption, enables shareholders to produce fake shares that are consistent with a target “fake message”, regardless of the original secret. In contrast to deniable encryption, in a DSS scheme an adversary sees multiple shares, some of which might be real, and some fake. This makes DSS a more difficult task, especially in situations where the fake shares need to be generated by individual shareholders, without coordination with other shareholders. We define several desirable properties for DSS, and show both positive and negative results for each. The strongest property is fake hiding, which is a natural analogy of deniability for encryption: given a complete set of shares, an adversary cannot determine whether any shares are fake. We show a construction based on Shamir secret sharing that achieves fake hiding as long as (1) the fakers are qualified (number $t$ or more), and (2) the set of real shares which the adversary sees is unqualified. Next we show a construction based on indistinguishability obfuscation that relaxes condition (1) and achieves fake hiding even when the fakers are unqualified (as long as they comprise more than half of the shareholders). We also extend the first construction to provide the weaker property of faker anonymity for all thresholds. (Faker anonymity requires that given some real shares and some fake shares, an adversary should not be able to tell which are fake, even if it can tell that some fake shares are present.) All of these constructions require the fakers to coordinate in order to produce fake shares. On the negative side, we first show that fake hiding is unachievable when the fakers are a minority, even if the fakers coordinate. Further, if the fakers do not coordinate, then even faker anonymity is unachievable as soon as $t < n$ (namely the reconstruction threshold is smaller than the number of parties).

In this paper, we present a ring referral scheme, by which a user can publicly prove her knowledge of a valid signature for a private message that is signed by one of an ad hoc set of authorized issuers, without revealing the signing issuer. Ring referral is a natural extension to traditional ring signature by allowing a prover to obtain a signature from a third-party signer. Our scheme is useful for diverse applications, such as certificate-hiding decentralized identity, privacy-enhancing federated authentication, anonymous endorsement and privacy -preserving referral marketing. In contrast with prior issuer-hiding credential schemes, our ring referral scheme supports more distinguishing features, such as (1) public verifiability over an ad hoc ring, (2) strong user anonymity against collusion among the issuers and verifier to track a user, (3) transparent setup, (4) message hiding, (5) efficient multi-message logarithmic verifiability, (6) threshold scheme for requiring multiple co-signing issuers. Finally, we implemented our ring referral scheme with extensive empirical evaluation

Due to their simple security assessments, permutation-based pseudo-random functions (PRFs) have become widely used in cryptography. It has been shown that PRFs using a single $n$-bit permutation achieve $n/2$ bits of security, while those using two permutation calls provide $2n/3$ bits of security in the classical setting. This paper studies the security of permutation-based PRFs within the Q1 model, where attackers are restricted to classical queries and offline quantum computations. We present improved quantum-time/classical-data tradeoffs compared with the previous attacks. Specifically, under the same assumptions/hardware as Grover's exhaustive search attack, i.e. the offline Simon algorithm, we can recover keys in quantum time $\tilde{O}(2^{n/3})$, with $O(2^{n/3})$ classical queries and $O(n^2)$ qubits. Furthermore, we enhance previous superposition attacks by reducing the data complexity from exponential to polynomial, while maintaining the same time complexity. This implies that permutation-based PRFs become vulnerable when adversaries have access to quantum computing resources. It is pointed out that the above quantum attack can be used to quite a few cryptography, including PDMMAC and pEDM, as well as general instantiations like XopEM, EDMEM, EDMDEM, and others.

As cloud computing continues to gain widespread adoption, safeguarding the confidentiality of data entrusted to third-party cloud service providers becomes a critical concern. While traditional encryption methods offer protection for data at rest and in transit, they fall short when it comes to where it matters the most, i.e., during data processing. To address this limitation, we present HELM, a framework for privacy-preserving data processing using homomorphic encryption. HELM automatically transforms arbitrary programs expressed in a Hardware Description Language (HDL), such as Verilog, into equivalent homomorphic circuits, which can then be efficiently evaluated using encrypted inputs. HELM features three modes of encrypted evaluation: a) a gate mode that consists of Boolean gates, b) a small-precision lookup table mode which significantly reduces the size of the circuit by combining multiple gates into lookup tables, and c) a high-precision lookup table mode tuned for multi-bit arithmetic evaluations. Finally, HELM introduces a scheduler that leverages the parallelism inherent in arithmetic and Boolean circuits to efficiently evaluate encrypted programs. We evaluate HELM with the ISCAS'85 and ISCAS'89 benchmark suites, as well as real-world applications such as image filtering and neural network inference. In our experimental results, we report that HELM can outperform prior works by up to 65x.

Since the introduction of TLS 1.3, which includes X25519 and X448 as key exchange algorithms, one could expect that high efficient implementations for these two algorithms become important as the need for power efficient and secure IoT devices increases. Assembly optimised X25519 implementations for low end processors such as Cortex-M4 have existed for some time but there has only been scarce progress on optimised X448 implementations for low end ARM processors such as Cortex-M4 and Cortex-M33. This work attempts to fill this gap by demonstrating how to design a constant time X448 implementation that runs in 2 273 479 cycles on Cortex-M4 and 2 170 710 cycles on Cortex-M33 with DSP. An X25519 implementation is also presented that runs in 441 116 cycles on Cortex-M4 and 411 061 cycles on Cortex-M33 with DSP.

Solitary output secure computation allows a set of mutually distrustful parties to compute a function of their inputs such that only a designated party obtains the output. Such computations should satisfy various security properties such as correctness, privacy, independence of inputs, and even guaranteed output delivery. We are interested in full security, which captures all of these properties. Solitary output secure computation has been the study of many papers in recent years, as it captures many real-world scenarios. A systematic study of fully secure solitary output computation was initiated by Halevi et al. [TCC 2019]. They showed several positive and negative results, however, they did not characterize what functions can be computed with full security. Alon et al. [EUROCRYPT 2024] considered the special, yet important case, of three parties with Boolean output, where the output-receiving party has no input. They completely characterized the set of such functionalities that can be computed with full security. Interestingly, they also showed a possible connection with the seemingly unrelated notion of fairness, where either all parties obtain the output or none of them do. We continue this line of investigation and study the set of three-party solitary output Boolean functionalities where all parties hold private inputs. Our main contribution is defining and analyzing a family of ``special-round'' protocols, which generalizes the set of previously proposed protocols. Our techniques allow us to identify which special-round protocols securely compute a given functionality (if such exists). Interestingly, our analysis can also be applied in the two-party setting (where fairness is an issue). Thus, we believe that our techniques may prove useful in additional settings and deepen our understanding of the connections between the various settings.

Following work of Mazur-Tate and Satoh, we extend the definition of division polynomials to arbitrary isogenies of elliptic curves, including those whose kernels do not sum to the identity. In analogy to the classical case of division polynomials for multiplication-by-n, we demonstrate recurrence relations, identities relating to classical elliptic functions, the chain rule describing relationships between division polynomials on source and target curve, and generalizations to higher dimension (i.e., elliptic nets).

Side-channel attacks pose significant threats to cryptographic implementations, which require the inclusion of countermeasures to mitigate these attacks. In this work, we study the masking of state-of-the-art post-quantum signatures based on the MPC-in-the-head paradigm. More precisely, we focus on the recent threshold-computation-in-the-head (TCitH) framework that applies to some NIST candidates of the post-quantum standardization process. We first provide an analysis of side-channel attack paths in the signature algorithms based on the TCitH framework. We then explain how to apply standard masking to achieve a $d$-probing secure implementation of such schemes, with performance scaling in $O(d^{2})$, for $d$ the masking order. Our main contribution is to introduce different ways to tweak those signature schemes towards their masking friendliness. While the TCitH framework comes in two variants, the GGM variant and the Merkle tree variant, we introduce a specific tweak for each of these variants. These tweaks allow us to achieve complexities of $O(d)$ and $O(d \log d)$ at the cost of non-constant signature size, caused by the inclusion of additional seeds in the signature. We also propose a third tweak that takes advantage of the threshold secret sharing used in TCitH. With the right choice of parameters, we show how, by design, some parts of the TCitH algorithms satisfy probing security without additional countermeasures. While this approach can substantially reduce the cost of masking in some part of the signature algorithm, it degrades the soundness of the core zero-knowledge proof, hence slightly increasing the size of the signature. We analyze the complexity of the masked implementations of our tweaked TCitH signatures and provide benchmarks on a RISC-V platform with built-in hash accelerator. We use a modular benchmarking approach, allowing to estimate the performance of diverse signature instances with different tweaks and parameters. Our results illustrate how the different variants scale for an increasing masking order. For instance, for a masking order $d = 3$, we obtain signatures of around $14$ kB that run in $0.67$ second on a the target RISC-V CPU with a $250$MHz frequency. This is to be compared with the $4.7$ seconds required by the original signature scheme masked at the same order on the same platform. For a masking order $d=7$, we obtain a signature of $17.5$ kB running in $1.75$ second, to be compared with $16$ seconds for the stardard masked signature. Finally, we discuss the extension of our techniques to signature schemes based on the VOLE-in-the-Head framework, which shares similarities with the GGM variant of TCitH. One key takeaway of our work is that the Merkle tree variant of TCitH is inherently more amenable to efficient masking than frameworks based on GGM trees, such as TCitH-GGM or VOLE-in-the-Head.

Efficiently protecting embedded software implementations of standard symmetric cryptographic primitives against side-channel attacks has been shown to be a considerable challenge in practice. This is, in part, due to the most natural countermeasure for such ciphers, namely Boolean masking, not amplifying security well in the absence of sufficient physical noise in the measurements. So-called prime-field masking has been demonstrated to provide improved theoretical guarantees in this context, and the Feistel for Prime Masking (FPM) family of Tweakable Block Ciphers (TBCs) has been recently introduced (Eurocrypt’24) to efficiently leverage these advantages. However, it was so far only instantiated for and empirically evaluated in a hardware implementation context, by using a small (7-bit) prime modulus. In this paper, we build on the theoretical incentive to increase the field size to obtain improved side-channel (Eurocrypt’24) and fault resistance (CHES’24), as well as on the practical incentive to instantiate an FPM instance with optimized performance on 32-bit software platforms. We introduce mid-pSquare for this purpose, a lightweight TBC operating over a 31-bit Mersenne prime field. We first provide an in-depth black box security analysis with a particular focus on algebraic attacks – which, contrary to the cryptanalysis of instances over smaller primes, are more powerful than statistical ones in our setting. We also design a strong tweak schedule to account for potential related-tweak algebraic attacks which, so far, are almost unknown in the literature. We then demonstrate that mid-pSquare implementations deliver very competitive performance results on the target platform compared to analogous binary TBCs regardless of masked or unmasked implementation (we use fix-sliced SKINNY for our comparisons). Finally, we experimentally establish the side-channel security improvements that masked mid-pSquare can lead to, reaching unmatched resistance to profiled horizontal attacks on lightweight 32-bit processors (ARM Cortex-M4).

Many lattice-based crypstosystems employ ideal lattices for high efficiency. However, the additional algebraic structure of ideal lattices usually makes us worry about the security, and it is widely believed that the algebraic structure will help us solve the hard problems in ideal lattices more efficiently. In this paper, we study the additional algebraic structure of ideal lattices further and find that a given ideal lattice in a polynomial ring can be embedded as an ideal into infinitely many different polynomial rings by the coefficient embedding. We design an algorithm to verify whether a given full-rank lattice in $\mathbb{Z}^n$ is an ideal lattice and output all the polynomial rings that the given lattice can be embedded into as an ideal with bit operations $\mathcal{O}(n^3(\log n + B)^2(\log n)^2)$, where $n$ is the dimension of the lattice and $B$ is the upper bound of the bit length of the entries of the input lattice basis. We would like to point out that Ding and Lindner proposed an algorithm for identifying ideal lattices and outputting a single polynomial ring of which the input lattice can be regarded as an ideal with bit operations $\mathcal{O}(n^5B^2)$ in 2007. However, we find a flaw in Ding and Lindner's algorithm, and it causes some ideal lattices can't be identified by their algorithm.

X-Wing is a hybrid key-encapsulation mechanism based on X25519 and ML-KEM-768. It is designed to be the sensible choice for most applications. The concrete choice of X25519 and ML-KEM-768 allows X-Wing to achieve improved efficiency compared to using a generic KEM combiner. In this paper, we introduce the X-Wing hybrid KEM construction and provide a proof of security. We show (1) that X-Wing is a classically IND-CCA secure KEM if the strong Diffie-Hellman assumption holds in the X25519 nominal group, and (2) that X-Wing is a post-quantum IND-CCA secure KEM if ML-KEM-768 is itself an IND-CCA secure KEM and SHA3-256 is secure when used as a pseudorandom function. The first result is proved in the ROM, whereas the second one holds in the standard model. Loosely speaking, this means X-Wing is secure if either X25519 or ML-KEM-768 is secure. We stress that these security gaurantees and optimizations are only possible due to the concrete choices that were made, and it may not apply in the general case.