International Association
for Cryptologic Research

The cube attack is a powerful cryptanalysis technique against symmetric ciphers, especially stream ciphers. The adversary aims to recover secret key bits by solving equations that involve the key. To simplify the equations, a set of plaintexts called a cube is summed up together. Traditional cube attacks use only linear or quadratic superpolies, and the size of cube is limited to an experimental range, typically around 40. However, cube attack based on division property, proposed by Todo et al. at CRYPTO 2017, overcomes these limitations and enables theoretical cube attacks on many lightweight stream ciphers. For a given cube $I$, they evaluate the set $J$ of secret key bits involved in the superpoly and require $2^{|I|+|J|}$ encryptions to recover the superpoly. However, the secret variables evaluation method proposed by Todo et al. sometimes becomes unresponsive and fails to solve within a reasonable time. In this paper, we propose an improvement to Todo's method by breaking down difficult-to-solve problems into several smaller sub-problems. Our method retains the efficiency of Todo's method while effectively avoiding unresponsive situations. We apply our method to the WAGE cipher, an NLFSR-based authenticated encryption algorithm and one of the second round candidates in the NIST LWC competition. Specifically, we successfully mount cube attacks on 29-round WAGE, as well as on 24-round WAGE with a sponge constraint. To the best of our knowledge, this is the first cube attack against the WAGE cipher, which provides a more accurate characterization of the WAGE's resistance against algebraic attacks.

Bulletin boards (BB) are important cryptographic building blocks that, at their core, provide a broadcast channel with memory. BBs are widely used within many security protocols, including secure multi-party computation protocols, e-voting systems, and electronic auctions. Even though the security of protocols crucially depends on the underlying BB, as also highlighted by recent works, the literature on constructing secure BBs is sparse. The so-far only provably secure BBs require trusted components and sometimes also networks without message loss, which makes them unsuitable for applications with particularly high security needs where these assumptions might not always be met.

In this work, we fill this gap by leveraging the concepts of accountability and universal composability (UC). More specifically, we propose the first ideal functionality for accountable BBs that formalizes the security requirements of such BBs in UC. We then propose Fabric$^\ast_\text{BB}$ as a slight extension designed on top of Fabric$^\ast$, which is a variant of the prominent Hyperledger Fabric distributed ledger protocol, and show that Fabric$^\ast_\text{BB}$ UC-realizes our ideal BB functionality. This result makes Fabric$^\ast_\text{BB}$ the first provably accountable BB, an often desired, but so far not formally proven property for BBs, and also the first BB that has been proven to be secure based only on standard cryptographic assumptions and without requiring trusted BB components or network assumptions. Through an implementation and performance evaluation we show that Fabric$^\ast_\text{BB}$ is practical for many applications of BBs.

Decentralized Finance (DeFi) has witnessed remarkable growth and innovation, with Decentralized Exchanges (DEXes) playing a pivotal role in shaping this ecosystem. As numerous DEX designs emerge, challenges such as price inefficiency and lack of user privacy continue to prevail. This paper introduces a novel DEX design, termed COMMON, that addresses these two predominant challenges. COMMON operates as an order book, natively integrated with a shielded token pool, thus providing anonymity to its users. Through the integration of zk-SNARKs, order batching, and Multiparty Computation (MPC) COMMON allows to conceal also the values in orders. This feature, paired with users never leaving the shielded pool when utilizing COMMON, provides a high level of privacy. To enhance price efficiency, we introduce a two-stage order matching process: initially, orders are internally matched, followed by an open, permissionless Dutch Auction to present the assets to Market Makers. This design effectively enables aggregating multiple sources of liquidity as well as helps reducing the adverse effects of Maximal Extractable Value (MEV), by redirecting most of the MEV profits back to the users.

There are two popular ways to measure computational entropy in cryptography: (HILL) pseudoentropy and (Yao) incompressibility entropy. Both of these computational entropy notions are based on a natural intuition.

- A random variable $X$ has $k$ bits of pseudoentropy if there exists a random variable $Y$ that has $k$ bits 'real' entropy and $Y$ is computationally indistinguishable from $X$. - A random variable $X$ has $k$ bits of incompressibility entropy if $X$ cannot be efficiently compressed to less than $k$ bits.

It is also intuitive, that if a random variable has high pseudoentropy, then it should also have high incompressibility entropy, because a high-entropy distribution cannot be compressed.

However, the above intuitions are not precise. Does 'real entropy' refer to Shannon entropy or min-entropy? What kind of correctness do we require from the compressor algorithm? Different papers use slightly different variations of both pseudoentropy and incompressibility entropy.

In this note we study these subtle differences and see how they affect the parameters in the implication that pseudoentropy implies incompressibility.

In 2022, NIST selected Kyber and Dilithium as post-quantum cryptographic standard algorithms. The Number Theoretic Transformation (NTT) algorithm, which facilitates polynomial multiplication, has become a primary target for side-channel attacks. Among these, Correlation Power Analysis (CPA) attacks against NTT have received much attention, which aims to recover all the coefficients of the private key in NTT domain. The necessity to recover all these coefficients not only limits efficiency but also directly impacts the feasibility of such attacks. Thus, a crucial question emerges: can the remaining coefficients be recovered using only a subset of known ones? In this work, we respond affirmatively by introducing overdetermined system-based and SIS-assisted key recovery methods for both Dilithium and Kyber, tailored for scenarios with incomplete NTT domain private keys. The SIS-assisted method, by embedding NTT transform matrix into the SIS search problem, offers a complete key recovery with the minimum known coefficients in NTT domain. For Kyber512 and Dilithium2, only 64 and 32 coefficients are enough to recover a subset of the private key with 256 coefficients, respectively. Furthermore, we propose a parameter-adjustable CPA scheme to expedite the recovery of a single coefficient in NTT domain. Combining this CPA scheme with the SIS-assisted approach, we executed practical attacks on both unprotected and masked implementations of Kyber and Dilithium on an ARM Cortex-M4. The results demonstrate that we can recover a subset of 256 private key coefficients for Dilithium2 using 2,000 power traces in 0.5 minutes, while Kyber512 requires 0.4 minutes and 500 power traces. These attacks achieve a 400$\times$ speedup compared to the best-known attacks against Dilithium. Moreover, we successfully break the first-order mask implementations and explore the potential applicable to higher-order implementations.

We show that here standard decoding algorithms for generic linear codes over a finite field can speeded up by a factor which is essentially the size of the finite field by reducing it to a low weight codeword problem and working in the relevant projective space. We apply this technique to SDitH and show that the parameters of both the original submission and the updated version fall short of meeting the security requirements asked by the NIST.

Remote side-channel attacks on processors exploit hardware and micro-architectural effects observable from software measurements. So far, the analysis of micro-architectural leakages over physical side-channels (power consumption, electromagnetic field) received little treatment. In this paper, we argue that those attacks are a serious threat, especially against systems such as smartphones and Internet-of-Things (IoT) devices which are physically exposed to the end-user. Namely, we show that the observation of Dynamic Random Access Memory (DRAM) accesses with an electromagnetic (EM) probe constitutes a reliable alternative to time measurements in cache side-channel attacks. We describe the EVICT+EM attack, that allows recovering a full AES key on a T-Tables implementation with similar number of encryptions than state-of-the-art EVICT+RELOAD attacks on the studied ARM platforms. This new attack paradigm removes the need for shared memory and exploits EM radiations instead of high precision timers. Then, we introduce PRIME+EM, which goal is to reverse-engineer cache usage patterns. This attack allows to recover the layout of lookup tables within the cache. Finally, we present COLLISION+EM, a collision-based attack on a System-on-chip (SoC) that does not require malicious code execution, and show its practical efficiency in recovering key material on an ARM TrustZone application. Those results show that physical observation of the micro-architecture can lead to improved attacks.

Over years of the development of secure multi-party computation (MPC), many sophisticated functionalities have been made pratical and multi-dimensional operations occur more and more frequently in MPC protocols, especially in protocols involving datasets of vector elements, such as privacy-preserving biometric identification and privacy-preserving machine learning. In this paper, we introduce a new kind of correlation, called tensor triples, which is designed to make multi-dimensional MPC protocols more efficient. We will discuss the generation process, the usage, as well as the applications of tensor triples and show that it can accelerate privacy-preserving biometric identification protocols, such as FingerCode, Eigenfaces and FaceNet, by more than 1000 times.

While blockchain technologies leverage compelling characteristics in terms of decentralization, immutability, and transparency, user privacy in public blockchains remains a fundamental challenge that requires particular attention. This is mainly due to the history of all transactions being accessible and available to anyone, thus making it possible for an attacker to infer data about users that is supposed to remain private.

In this paper, we provide a threat model of possible privacy attacks on users utilizing the Bitcoin blockchain. To this end, we followed the LINDDUN GO methodology to identify threats and suggest possible mitigation.

Given a fixed-size block, cryptographic block functions gen- erate outputs by a sequence of bitwise operations. Block functions are widely used in the design of hash functions and stream ciphers. Their correct implementations hence are crucial to computer security. We pro- pose a method that leverages logic equivalence checking to verify assem- bly implementations of cryptographic block functions. Logic equivalence checking is a well-established technique from hardware verification. Using our proposed method, we verify two dozen assembly implementations of ChaCha20, SHA-256, and SHA-3 block functions from OpenSSL and XKCP automatically. We also compare the performance of our technique with the conventional SMT-based technique in experiments.

Deep Learning (DL) based Side-Channel Analysis (SCA) has been extremely popular recently. DL-based SCA can easily break implementations protected by masking countermeasures. DL-based SCA has also been highly successful against implementations protected by various trace desynchronization-based countermeasures like random delay, clock jitter, and shuffling. Over the years, many DL models have been explored to perform SCA. Recently, Transformer Network (TN) based model has also been introduced for SCA. Though the previously introduced TN-based model is successful against implementations jointly protected by masking and random delay countermeasures, it is not scalable to long traces (having a length greater than a few thousand) due to its quadratic time and memory complexity. This work proposes a novel shift-invariant TN-based model with linear time and memory complexity. The contributions of the work are two-fold. First, we introduce a novel TN-based model called EstraNet for SCA. EstraNet has linear time and memory complexity in trace length, significantly improving over the previously proposed TN-based model’s quadratic time and memory cost. EstraNet is also shift-invariant, making it highly effective against countermeasures like random delay and clock jitter. Secondly, we evaluated EstraNet on three SCA datasets of masked implementations with random delay and clock jitter effects. Our experimental results show that EstraNet significantly outperforms several benchmark models, demonstrating up to an order of magnitude reduction in the number of attack traces required to reach guessing entropy 1.

Explainable AI (XAI) refers to the development of AI systems and machine learning models in a way that humans can understand, interpret and trust the predictions, decisions and outputs of these models. A common approach to explainability is feature importance, that is, determining which input features of the model have the most significant impact on the model prediction. Two major techniques for computing feature importance are LIME (Local Interpretable Model-agnostic Explanations) and SHAP (SHapley Additive exPlanations). While very generic, these methods are computationally expensive even in plaintext. Applying them in the privacy-preserving setting when part or all of the input data is private is therefore a major computational challenge. In this paper, we present $\texttt{XorSHAP}$ - the first practical privacy-preserving algorithm for computing Shapley values for decision tree ensemble models in the semi-honest Secure Multiparty Computation (SMPC) setting with full threshold. Our algorithm has complexity $O(T \widetilde{M} D 2^D)$, where $T$ is the number of decision trees in the ensemble, $D$ is the depth of the decision trees and $\widetilde{M}$ is the maximum of the number of features $M$ and $2^D$ (the number of leaf nodes of a tree), and scales to real-world datasets. Our implementation is based on Inpher's $\texttt{Manticore}$ framework and simultaneously computes (in the SMPC setting) the Shapley values for 100 samples for an ensemble of $T = 60$ trees of depth $D = 4$ and $M = 100$ features in just 7.5 minutes, meaning that the Shapley values for a single prediction are computed in just 4.5 seconds for the same decision tree ensemble model. Additionally, it is parallelization-friendly, thus, enabling future work on massive hardware acceleration with GPUs.

zkSNARK is a cryptographic primitive that allows a prover to prove to a resource constrained verifier, that it has indeed performed a specified non-deterministic computation correctly, while hiding private witnesses. In this work we focus on lattice based zkSNARK, as this serves two important design goals. Firstly, we get post-quantum zkSNARK schemes with $O(\log (\mbox{Circuit size}))$ sized proofs (without random oracles) and secondly, the easy verifier circuit allows further bootstrapping by arbitrary (zk)SNARK schemes that offer additional or complementary properties. However, this goal comes with considerable challenges. The only known lattice-based bilinear maps are obtained using multi-linear maps of Garg, Gentry, and Halevi 2013 (GGH13), which have undergone considerable cryptanalytic attacks, in particular annihilation attacks.

In this work, we propose a (level-2) GGH13-encoding based zkSNARK which we show to be secure in the weak-multilinear map model of Miles-Sahai-Zhandry assuming a novel pseudo-random generator (PRG). We argue that the new PRG assumption is plausible based on the well-studied Newton's identity on power-sum polynomials, as well as an analysis of hardness of computing Grobner bases for these polynomials. The particular PRG is designed for efficient implementation of the zkSNARK.

Technically, we leverage the 2-linear instantiation of the GGH13 graded encoding scheme to provide us with an analogue of bilinear maps and adapt the Groth16 (Groth, Eurocrypt 2016) protocol, although with considerable technical advances in design and proof. The protocol is non-interactive in the CRS model.

In this work, we propose a simple framework of constructing efficient non-interactive zero-knowledge proof (NIZK) systems for all NP. Compared to the state-of-the-art construction by Groth, Ostrovsky, and Sahai (J. ACM, 2012), our resulting NIZK system reduces the proof size and proving and verification cost without any trade-off, i.e., neither increasing computation cost, CRS size nor resorting to stronger assumptions. Furthermore, we extend our framework to construct a batch argument (BARG) system for all NP. Our construction remarkably improves the efficiency of BARG by Waters and Wu (Crypto 2022) without any trade-off.

Threshold Implementation (TI) is a well-known Boolean masking technique that provides provable security against side-channel attacks. In the presence of glitches, the probing model was replaced by the so-called glitch-extended probing model which specifies a broader security framework. In CHES 2021, Shahmirzadi et al. introduced a general search method for finding first-order 2-share TI schemes without fresh randomness (under the presence of glitches) for a given encryption algorithm. Although it handles well single-output Boolean functions, this method has to store output shares in registers when extended to vector Boolean functions, which results in more chip area and increased latency. Therefore, the design of TI schemes that have low implementation cost under the glitch-extended probing model appears to be an important research challenge. In this paper, we propose an approach to design the first-order glitch-extended probing secure TI schemes when quadratic functions are employed in the substitution layer. This method only requires a small amount of fresh random bits and a single clock cycle for its implementation. In particular, the random bits in our approach are reusable and compatible with the changing of the guards technique. Our dedicated TI scheme for the AES cipher gives 20.23% smaller implementation area and 4.2% faster encryption compared to the TI scheme of AES (without using fresh randomness) proposed in CHES 2021. Additionally, we propose a parallel implementation of two S-boxes that further reduces latency (about 39.83%) at the expense of increasing the chip area by 9%. We have positively confirmed the security of AES under the glitch-extended probing model using the verification tool - SILVER and the side-channel leakage assessment method - TVLA.

Decentralized Finance, mushrooming in permissionless blockchains, has attracted a recent surge in popularity. Due to the transparency of permissionless blockchains, opportunistic traders can compete to earn revenue by extracting Miner Extractable Value (MEV), which undermines both the consensus security and efficiency of blockchain systems. The Flashbots bundle mechanism further aggravates the MEV competition because it empowers opportunistic traders with the capability of designing more sophisticated MEV extraction. In this paper, we conduct the first systematic study on DeFi MEV activities in Flashbots bundle by developing ActLifter, a novel automated tool for accurately identifying DeFi actions in transactions of each bundle, and ActCluster, a new approach that leverages iterative clustering to facilitate us to discover known/unknown DeFi MEV activities. Extensive experimental results show that ActLifter can achieve nearly 100% precision and recall in DeFi action identification, significantly outperforming state-of-the-art techniques. Moreover, with the help of ActCluster, we obtain many new observations and discover 17 new kinds of DeFi MEV activities, which occur in 53.12% of bundles but have not been reported in existing studies.

The general quantum approximate optimization algorithm (QAOA) produces approximate solutions for combinatorial optimization problems. The algorithm depends on a positive integer $p$ and the quality of approximation improves as $p$ is increased. In this note, we put some questions about the general QAOA. We also find the recursive QAOA for MaxCut problem is flawed because all quantum gates involved in the algorithm are single qubit gates. No any entangling gate is used, which results in that the quantum computing power cannot be certified for the problem.

This report analyzes the 16 submissions to the Korean post-quantum cryptography (KpqC) competition.

The security of code-based cryptography relies primarily on the hardness of decoding generic linear codes. Until very recently, all the best algorithms for solving the decoding problem were information set decoders ($\mathsf{ISD}$). However, recently a new algorithm called RLPN-decoding which relies on a completely different approach was introduced and it has been shown that RLPN outperforms significantly $\mathsf{ISD}$ decoders for a rather large range of rates. This RLPN decoder relies on two ingredients, first reducing decoding to some underlying LPN problem, and then computing efficiently many parity-checks of small weight when restricted to some positions. We revisit RLPN-decoding by noticing that, in this algorithm, decoding is in fact reduced to a sparse-LPN problem, namely with a secret whose Hamming weight is small. Our new approach consists this time in making an additional reduction from sparse-LPN to plain-LPN with a coding approach inspired by $\mathsf{coded}$-$\mathsf{BKW}$. It outperforms significantly the $\mathsf{ISD}$'s and RLPN for code rates smaller than $0.42$. This algorithm can be viewed as the code-based cryptography cousin of recent dual attacks in lattice-based cryptography. We depart completely from the traditional analysis of this kind of algorithm which uses a certain number of independence assumptions that have been strongly questioned recently in the latter domain. We give instead a formula for the LPN noise relying on duality which allows to analyze the behavior of the algorithm by relying only on the analysis of a certain weight distribution. By using only a minimal assumption whose validity has been verified experimentally we are able to justify the correctness of our algorithm. This key tool, namely the duality formula, can be readily adapted to the lattice setting and is shown to give a simple explanation for some phenomena observed on dual attacks in lattices in [DP23].

The existence of a quantum computer is one of the most significant threats cryptography has ever faced. However, it seems that real world protocols received little attention so far with respect to their future security. Indeed merely relying upon post-quantum primitives may not suffice in order for a security protocol to be resistant in a full quantum world. In this paper, we consider the fundamental UMTS key agreement used in 3G but also in 4G (LTE), and in the (recently deployed) 5G technology. We analyze the protocol in a quantum setting, with quantum communications (allowing superposition queries by the involved parties), and where quantum computation is granted to the adversary. We prove that, assuming the underlying symmetric-key primitive is quantum-secure, the UMTS key agreement is also quantum-secure. We also give a quantum security analysis of the underlying primitives, namely Milenage and TUAK. To the best of our knowledge this paper provides the first rigorous proof of the UMTS key agreement in a strong quantum setting. Our result shows that in the quantum world to come, the UMTS technology remains a valid scheme in order to secure the communications of billions of users.