International Association
for Cryptologic Research

Recent advances in quantum computing threaten the cryptographic foundations of blockchain systems, including Bitcoin and Ethereum, which rely on elliptic-curve cryptography (ECC) for security. Algorithms such as Shor's algorithm can efficiently solve the discrete logarithm problem (DLP), enabling recovery of private keys from public keys. Existing funds, especially those tied to long-lived addresses or unspent coinbase outputs (such as Satoshi Nakamoto's bitcoins), and Ethereum externally owned accounts become vulnerable once large-scale quantum computers become available. While previous work has suggested various post-quantum signature schemes and migration strategies, no widely deployed, end-to-end, backward-compatible, and privacy-preserving migration mechanism has been presented for migrating legacy funds without revealing the corresponding classical public keys on-chain.

In this paper, we present a complete framework that enables secure migration of both spent and unspent funds to a post-quantum security model, using a hybrid approach based on post-quantum signatures and quantum-resistant zero-knowledge proofs (ZKPs). By integrating classical and post-quantum cryptography with quantum-safe proofs, we protect blockchain systems against quantum-era adversaries while preserving asset security, protocol compatibility, and operational continuity. Our method supports two distinct migration scenarios (depending on whether public keys have been revealed) and applies uniformly to both Bitcoin's UTXO model and Ethereum's account-based model. We design zkSTARK circuits that prove knowledge of a witness linking a legacy address to a fresh PQ public key without disclosing the legacy private key. To enable decentralized and verifiable on-chain transitions, we propose new primitives (\texttt{OP\_CHECKQUANTUMSIG}, \texttt{OP\_CHECKSTARKPROOF}) for Bitcoin and Ethereum, enabling verification of quantum-safe proofs and signatures. Our work and implementation \footnote{\href{https://github.com/skardas/pq_bitcoin}{\texttt{github.com/skardas/pq\_bitcoin}}} provides a practical and efficient framework for securing legacy blockchain assets against quantum-era threats, while preserving backward compatibility and availability.

In 2006 de Graaf et al. devised a Lie-algebra-based strategy for finding a linear transformation $T \in PGL_{N+1}(\mathbb{Q})$ connecting two linearly equivalent projective varieties $X, X' \subseteq \mathbb{P}^N$ over $\mathbb{Q}$. The method succeeds for several families of "classical" varieties such as Veronese varieties, which have large automorphism groups. In this paper, we study the Lie algebra method over finite fields, which comes with new technicalities when compared to $\mathbb{Q}$ due to, e.g., the characteristic being positive. Concretely, we make the method work for Veronese varieties of dimension $r \geq 2$ and (heuristically) for secant varieties of Grassmannians of planes. This leads to classical polynomial-time attacks against two candidate-post-quantum key exchange protocols based on disguised Veronese surfaces and threefolds, which were recently proposed by Alzati et al., as well as a digital signature scheme based on secant varieties of Grassmannians of planes due to Di Tullio and Gyawali. We provide an implementation in Magma.

Hybrid cryptographic schemes combine multiple primitives to provide resilience against diverse threats, particularly in the post-quantum era where classical algorithms face potential quantum attacks. However, existing hybrid approaches rely on predefined, fixed pairings of specific cryptographic algorithms, limiting their adaptability to evolving security requirements and heterogeneous deployment environments. This paper presents a generalized framework for the hybridization of cryptographic primitives that enables dynamic, user-driven composition of encryption schemes and digital signatures. Our approach leverages all-or-nothing transformations (AONTs) to construct hybrid schemes where an adversary must break all constituent primitives simultaneously to compromise the system. We formally prove that if at least one component scheme remains secure (IND-CPA for encryption, EUF-CMA for signatures), the entire hybrid construction achieves security equivalent to its strongest component. Unlike conventional approaches that prescribe specific algorithm combinations, our framework allows flexible selection and integration of classical, post-quantum, or mixed cryptographic primitives based on specific security requirements, computational constraints, and threat models. Our generalized hybridization methodology naturally extends to key encapsulation mechanisms and other cryptographic primitives, providing a foundation for building future adaptive cryptographic systems that remain secure even as individual components are compromised over time. This addresses a critical gap in current cryptographic practices and will provide users a methodology to construct flexible, robust security architectures for the post-quantum era.

In this paper, we propose a generalized model of Priority Arbiter-based Physical Unclonable Function (PA-PUF) with an arbitrary number of paths inside each switch. We first develop a mathematical model for this generalized model. Experimentally, we observed that the class of Boolean functions generated from our model of PA-PUF increases proportionally with the number of paths inside each switch, and that motivated us to attempt one of the open challenges proposed by Kansal et al. [DAM 2024]. We first show that the set of Boolean functions generated from $i$-length PA-PUF with $(i+1)$ number of paths is a proper super set of the set of Boolean functions generated from $i$-length PA-PUF with $i$ number of paths. Based upon that, we show in our main result that we need at least $(n+1)$ numbers of paths inside each switch of an $n$-length PA-PUF to generate all the Boolean functions involving $n$-number of variables. Furthermore, we performed significant software and hardware experimentations to assess the resilience of our model against machine learning based modeling attacks.

SAE and SAE-PK are the core security protocols introduced in the latest Wi-Fi security standard, WPA3, to protect personal networks. SAE-PK extends SAE to prevent the so-called evil twin attacks, where an attacker with the knowledge of the password attempts to impersonate a legitimate access point. In this work, we present the first provable security and privacy analysis of SAE and SAE-PK. We introduce formal models that capture their intended properties and use these models to analyze the guarantees these protocols provide.

First, we identify an attack that prevents SAE from fulfilling its intended authentication guarantees. As a result, SAE can only be proven secure within a weaker security model, which we also formalize and show the proof in. To achieve the desired level of security, we propose two simple fixes, resulting in two efficient SAE protocols that we call SAEv2 and SAEv3. We prove that both protocols meet the intended security guarantees, with SAEv3 providing greater robustness.

Next, we prove that SAE-PK is indeed secure against evil twin attacks, but its current design introduces a theoretical vulnerability to offline dictionary attacks, which contradicts the expected security guarantees of SAE-PK as an enhanced password-authenticated key exchange protocol. To remedy this, we show that SAE-PK can be modified with minimal changes to fully realize its desired security goals.

Finally, we analyze the privacy guarantees of SAE, SAE-PK, and our proposed enhanced variants. We prove that their cryptographic core preserves the unlinkability of client devices across distinct Wi-Fi networks, if MAC address randomization is properly applied.

\emph{Modular Polynomial Commitment Schemes (Mod-PCS)} extend standard PCSs by enabling provable evaluation of integer polynomials modulo a random modulus, providing a natural foundation for SNARKs that operate directly over large integers without emulating arithmetic in finite fields. Only two Mod-PCS constructions are known. The first (Campanelli and Hall-Andersen, IACR ePrint 2024) serves primarily as a feasibility result and is impractical and not post-quantum secure due to its reliance on groups of unknown order. The second (Garetta et al., CRYPTO 2025) introduces the weaker notion of \emph{relaxed} Mod-PCS, but is not fully succinct: committing to a multilinear polynomial with $N$ terms and $B$-bit coefficients requires $O(\sqrt{N}B)$ proof size and verification time.

We present a black-box transformation that builds relaxed Mod-PCS from any standard PCS, enabling new constructions. Instantiating our transformation with a tensor-code PCS yields the first relaxed Mod-PCS with $O(\log (N+B))$ proof size and verifier time, which is transparent and plausibly post-quantum secure. Using this scheme within the framework of Garetta et al., we obtain the first fully succinct SNARK for the Customizable Constraint System over $\mathbb{Z}_B$, achieving $O(B\log N + N\log N \log B)$ prover time and $O(\log (N+B))$ verifier time and proof size.

Our approach relies on a commitment-switching technique for integer polynomials and a new batched integer commitment scheme from any PCS. We further introduce improved arguments for integer addition and multiplication, correctness of the number-theoretic transform, and general Diophantine relations over committed integers.

Secure aggregation is a core primitive for privacy-preserving federated learning, enabling a server to compute aggregates of client updates without learning individual inputs. Recent protocols have explored committee-based designs to reduce client overhead and tolerate weakly connected participants. However, existing approaches still incur communication and computation costs that scale with the number of clients and/or the size of model updates. This becomes a serious bottleneck in interaction between the server and the committee, given that model updates are high-dimensional and committee is a small set of clients.

We present Lighthouse, a new secure aggregation protocol that supports one-shot client communication and achieves constant committee computation and communication overhead with server, independent of both the number of clients and the size of the input vector. Our protocol attains the best-known round complexity of two rounds, matching OPA (CRYPTO 2025) and TACITA (ePrint 2025) and improving upon Flamingo (IEEE S&P 2023) and Willow (CRYPTO 2025). Our core technical contribution is a novel application of recent advances in batched threshold encryption, which enables succinct server–committee interaction while preserving security and correctness. Beyond asymptotic improvements over prior works, Lighthouse yields substantial concrete efficiency gains: For an aggregation with 1024 clients, we reduce server-to-committee communication by over 100× and committee-to-server communication by over 300× compared to Flamingo and Willow. Also, we present an extension that supports dynamic client participation, a critical requirement for practical deployments at scale, while preserving the asymptotic and concrete efficiency of the static protocol for clients.

Garbled RAM is a promising technique for scaling secure two-party computation to large datasets. It features an efficient two-round protocol and supports each memory access with polylogarithmic overhead, thereby avoiding the prohibitive cost of RAM-to-circuit conversion. While earlier works on Garbled RAM primarily focused on establishing theoretical feasibility, recent research has increasingly emphasized concrete efficiency, culminating in constructions that achieve approximately $O(\lambda T W \log N)$ bandwidth cost (up to super-constant factors) for garbling a RAM with running time $T$, memory size $N$, and word size $W$.

We ask whether it is possible to further improve the bandwidth cost of Garbled RAM. In contrast, the Garbled Circuit literature has developed a rich set of techniques that remove the bandwidth's dependence on the security parameter $\lambda$, leading to constant-rate or even sub-constant-rate garbling schemes. However, no comparable methods are currently known for Garbled RAM.

We propose a new garbling scheme for arithmetic RAM, called Zebra (short for ``Zero Exposure B-bounded Random Accesses''). Specifically, we show that when the word size $W$ is suitably large, we can eliminate the $\lambda$-factor dependence and achieve a bandwidth cost of $O(T W \log N)$. In this sense, our scheme can also be viewed as the RAM analogue of ``constant-rate garbling for arithmetic circuits''. Further, we show how to extend our techniques to support the garbling of boolean RAMs, achieving a bandwidth cost of $O(T W (\log N + \lambda))$ when the word size is suitably large. We implemented Zebra and released our code through open source. Our evaluation shows a $10.1\times$ concrete improvement in bandwidth and a $3.5\times$ improvement in end-to-end time relative to the state-of-the-art Garbled RAM schemes on a 256MB database with 4kB entries.

AMD Versal FPGAs introduce a new CLB microarchitecture in which legacy CARRY4/8 chains are replaced by LOOKAHEAD8 structures. Existing area-efficient LUT-based multiplier designs typically rely on CARRY4/8 primitives from prior FPGA generations. On Versal devices, these designs exhibit poor mapping efficiency. This paper proposes a new LUT-based integer multiplier architecture tailored to Versal fabric, together with an automated RTL generator supporting arbitrary operand bit-widths and configurable pipeline depths. Through the joint exploitation of radix-4 modified Booth recoding and the new micro-architectural features of Versal LUTs, only ∼$n^2/4$ LUTs are required to generate the partial-product bit heap for an nbit multiplication. Moreover, a new heuristic is developed for compressor tree synthesis to sum the bit heap, yielding an 8–20% improvement in area–delay product compared with state-of-theart heuristics for Versal devices. Overall, the proposed multipliers achieve up to 40% LUT footprint reduction relative to AMD LogiCORE IP multipliers while maintaining comparable criticalpath delay. The proposed generator enables scalable and customizable deployment of resource-efficient bit heap compressors and integer multipliers for Versal-based accelerator designs.

Physical attacks are a well-known threat for otherwise secure implementations of cryptographic algorithms. Although attacks and countermeasures for Side-Channel Analysis (SCA) and Fault-Injection Analysis (FIA) are well studied and individually understood, their combined exploitation and the corresponding countermeasures remain a relatively new area of research. Just recently, Feldtkeller et al. presented Combined Private Circuit (CPC) gadgets at CCS 2022 and CCS 2023 which were the first provably secure combined hardware gadgets that adhere to the notion of Combined-Isolating Non-Interference (CINI). The definition of the CINI notion has been a milestone for the development and formal verification of combined secure gadgets. However, it is also specifically tailored to the realization of side-channel resistance via plain masking and redundancy via replication, without further considerations of other constructions, e.g., those based on coding theory. In this work, we extend the existing definition of CINI to the notion of generalized Combined Isolated Non-Interfering (gCINI). Our generalizations allow to capture a much wider range of possible encodings, including - but not limited to - Boolean masking and replication, and provide a formal basis for the analysis of more general gadget constructions. We formally prove the combined security and composability of our new gCINI definition and give an explicit way to build such gadgets. The significance of our proposed construction is demonstrated through the implementation of several use cases, including an AES S-box design that outperforms comparable CPC-based approaches while maintaining the same level of combined security. Finally, we formally verify the security of our gadget constructions using an adapted version of VERICA.

The Middle Product Learning With Errors (MP-LWE) problem was introduced in 2017 by Rosca, Sakzad, Steinfeld, and Stehlé (Crypto 2017). In their work and in a follow up work by Rosca, Stehlé, and Wallet (Eurocrypt 2018), the authors proved that MP-LWE is at least as hard as the Ring-LWE problem over the field $\mathbb{Q}[x]/f(x)$, for an exponentially large class of polynomials $f$ (with fixed degree and bounded coefficients). A few years later, Peikert and Pepin gave a new reduction from Ring-LWE to MP-LWE (Journal of Cryptology 2024). This new reduction improved the results of Rosca et al. by increasing the set of polynomials $f$ for which the reduction holds. However, even though the sets of polynomials covered by both reductions have exponential size, they remain negligible among the set of all polynomials of fixed degree and bounded coefficients.

In this work, we provide a refined analysis of the reduction of Rosca et al. Our new analysis shows that the reduction of Rosca et al. actually covers a much larger class of polynomials than what was known before, containing (experimentally) at least $90\%$ of all polynomials of fixed degree and bounded coefficients.

We study the syndrome decoding problem (SDP) in the presence of side information. The SDP asks, given a binary parity-check matrix $\mathbf{H}$ and a syndrome $\mathbf{s}$, to find a low Hamming weight binary error $\mathbf{e}$ such that $\mathbf{H} \mathbf{e} = \mathbf{s}$ over $\mathbb{F}_2$. Recent work (Cayrel et al., Eurocrypt '21) exploits a fault injection attack to reveal syndrome entries over the integers, referred to as perfect hints. Subsequent works considered side-channel scenarios to reveal similar, but noisy, information (approximate hints).

Both types of hints have been shown empirically to allow for solving the SDP once enough of them are available. However, fundamental questions about the impact of these hints on the hardness of the SDP, such as thresholds for a collapse into the polynomial-time regime or how to exploit arbitrary amounts of hints, remain open.

In this work, we show that both types of hints effectively allow one to transform the SDP instance into a soft-decision decoding instance. We then adapt Information Set Decoding (ISD) algorithms, the best known technique to solve generic SDP instances, to this setting. In contrast to previous work, we obtain non-trivial speedups for any amount of available hints, interpolating smoothly between the complexity of standard ISD (no hints) and polynomial time (sufficient hints). Furthermore, our practical simulations show that Hint-ISD achieves the polynomial-time regime generally under fewer hints than previous approaches.

We then provide an explicit bound on the number of hints required to reach the polynomial-time regime. This bound confirms earlier practical observations that higher error weights, such as those found in the McEliece cryptosystem, exhibit higher resistance against hint exposure than schemes using smaller error weights, such as HQC.

The recent study has demonstrated that neural networks can serve as a navigator for an automatic search model for integral cryptanalysis with a reduction in computational complexity. However, the inherent drawbacks of using a deep learning model such as large datasets and limited interpretability are the major obstacles in cryptanalysis. In this paper, we introduce another simple data-driven approach using the linear algebraic concept to characterize key-independent balance properties as the kernel of a matrix with empirical parity data. For a fixed cipher, we stack the ciphertext parities obtained under many independent keys into the parity matrix and prove that every mask satisfying the matrix multiplication as zero corresponds exactly to a balance property. We demonstrate the practicality and generality of the kernel methodology on seven lightweight block ciphers spanning SPN and ARX designs. Across these cases, our method recovers known distinguishers and reveals additional non-trivial linear combinations missed by conventional analyses. We additionally position the kernel method relative to other similar methodologies. Our results show that the kernel method provides a rigorous and cipher-agnostic alternative to neural feature exploration and complements division property-based search techniques.

A structured vector range argument proves that a committed vector $\mathbf{v}$ lies in a well-structured range of the form $[0,2^d-1]$. This structure makes the protocol extremely efficient, although it cannot handle more sophisticated range assertions, such as those arising from non-membership attestations. To address this gap, we study a more general setting not captured by prior constructions. In this setting, for each $i$, the admissible integer set for $v_i$ is a union of $k$ intervals $\mathsf{R}_i \overset{\text{def}}{=} \bigcup_{j=0}^{k-1}\left[l_{i,j},r_{i,j}\right]$. In this work, we present novel techniques to prove that $\mathbf{v} \in \mathbb{Z}^n_p$ lies within $\mathsf{R}_0 \times \mathsf{R}_1 \times \cdots \times \mathsf{R}_{n-1}$. We first introduce $\mathsf{RangeLift}$, a generic compiler that lifts a structured vector range argument to support such unstructured range assertions. Then we present $\mathsf{Spectra}$, a realization of $\mathsf{RangeLift}$ over the $\mathsf{KZG}$-based vector commitment scheme. $\mathsf{Spectra}$ achieves succinct communication and verifier time; its prover complexity is $O(n\,\tfrac{\log N}{\log\log N}\cdot \log(n\tfrac{\log N}{\log\log N}))$, where $N$ upper bounds the maximum interval size across all $\mathsf{R}_i$. Notably, $\mathsf{Spectra}$ is interval-agnostic, meaning its prover complexity is independent of the number of intervals $k$; therefore, its prover cost matches the single-interval case even when each $\mathsf{R}_i$ is composed of hundreds of thousands of intervals. We also obtain two new structured vector range arguments and a batching-friendly variant of the $\mathsf{Cq}^{+}$ lookup argument (PKC'24), which are also of independent interest. Experiments show that $\mathsf{Spectra}$ outperforms well-known curve-based vector range arguments on standard metrics while supporting strictly more expressive range assertions.

This paper investigates a recent, claimed state-of-the-art attack on the ASCADv2 dataset, a higher-order masked and shuffled AES implementation, which we demonstrate to be a false positive. Despite successful validation using classical metrics, including a converging Guessing Entropy (GE), we prove that the model learned no actual side-channel leakage. Instead, it exploited a statistical bias in the intermediate value distribution.

We argue that the usual scoring function used in the GE is an unreliable metric in the presence of such biases. To address this critical evaluation flaw, we propose a set of methods to avoid falling in this pitfall. First, we introduce pre-emptive methods to detect significant biases in the target's value distribution before profiling, as well as post-mortem ones to examine the resulting model. Second, we present guidelines to avoid regimes where the GE is unreliable, and we derive the Asymptotically Optimal Distinguisher, a new, lightweight distinguisher that provably neutralizes the influence of learned priors in the GE metric, thereby isolating the information gained purely from the side-channel leakage. We demonstrate our methodology by successfully identifying the ASCADv2 false positive and applying it to synthetically biased versions of the ASCADv1 dataset.

Secure Multiparty Computation (MPC) computes on private input data, but generally does not guarantee correctness of the output towards third parties. This property, also called public auditability, was first studied explicitly by Baum et al. (SCN 2014). Their work and its follow-ups generate a Non-Interactive Zero-Knowledge proof of correctness of the MPC outcome during the MPC protocol, ensuring validity of the output even if all parties are corrupted.

In this work, we revisit and improve the MPC with Public Auditability blueprint. While the original work uses a version of the SPDZ MPC protocol with expensive lattice-based preprocessing, our construction combines any generic OLE-based preprocessing with a publicly verifiable somewhat linearly homomorphic commitment scheme from VOLE-in-the-head in a non-trivial way. Our commitment scheme relies solely on random oracle calls instead of previously used linearly homomorphic commitments based on structured Public-Key assumptions.

A vast body of work studies how to build a pseudorandom function (PRF) from a pseudorandom permutation (PRP) with beyond-the-birthday-bound (BBB) security. Often, such constructions are also expected to offer some security in keyless settings, for example in the context of committing security or to substitute a parallelizable short-input random oracle (RO) if used in counter mode. This has spurred several works on keyless variants of PRP-to-PRF constructions. However, recent works (Gunsing et al., CRYPTO 2022, 2023) reveal flaws in almost all existing proofs, painting a grim picture. This paper clarifies the situation with an in-depth analysis of RP-based short-input RF constructions.

First, we categorize all two-call short-input/output RP-to-RF constructions and evaluate their indifferentiability level. We introduce the "chaining attack'', a powerful, widely applicable differentiability attack. When applied to the sum of a permutation and its inverse, it invalidates an earlier result (Dodis et al., EUROCRYPT 2008). On the positive side, we show that only the Sum Of Permutations and Encrypted Davies-Meyer Dual, when instantiated with independent permutations, achieve BBB security and could potentially yield a parallelizable short-input RO.

Second, we study the indifferentiability of expanding RP-to-RF constructions and show that $\mathtt{XORP}_w$, the core PRF underlying $\textsf{CENC}$, achieves BBB security. As side effects, we obtain a simplified proof of indifferentiability for Sum of Permutations, and the committing security of $\textsf{CENC}$.

Simulation extractability ensures that any adversary who produces a valid proof must possess a corresponding witness, even after seeing simulated proofs for potentially false statements. This property is vital for preventing malleability attacks and is therefore essential for securely deploying zero-knowledge succinct non-interactive arguments of knowledge (zkSNARKs) in distributed systems. While prior work, particularly the frameworks by Faonio et al. (CCS’24, TCC’23) and Kohlweiss et al. (TCC’23), has established simulation extractability for a wide class of pairing-based zkSNARKs using the KZG univariate polynomial commitment scheme (Kate et al., Asiacrypt’10), we initiate a systematic study of simulation extractability for zkSNARKs based on the celebrated sumcheck protocol and the PST multivariate polynomial commitment scheme (Papamanthou et al., TCC’13). PST cannot be simulation extractable, due to its linear homomorphism, however, we show that it satisfies a refined notion of controlled malleability similar to the notion of Chase et al. (EUROCRYPT’12), which informally captures that linear homomorphism is essentially the only admissible malleability. We demonstrate that our notion of controlled malleability suffices to ensure security within the widely adopted design paradigm of compiling polynomial interactive oracle proofs into zkSNARKs, covering several state-of-the-art schemes such as HyperPlonk (EUROCRYPT’23), Spartan (CRYPTO’20) and Libra (CRYPTO’19).

We provide a new interpretation of the arithmetic on Hessian Kummer lines using level-3 theta structures. This allows us to break the record for tripling on elliptic curves and their Kummer lines, requiring only 4 multiplications and 4 squarings per tripling for well-chosen curve parameters.

We initiate study on how to build a rigorous, cryptographic foundation for *proofs of personhood* - convincing, privacy-preserving evidence that a digital participant is a real, unique, and reputable human, optionally with authenticated attributes such as age or institutional affiliation. Towards this goal, we introduce a framework based on two types of credentials: *personhood credentials* (PHCs), issued by trusted authorities to attest to uniqueness and basic attributes, and *verifiable relationship credentials* (VRCs), issued peer-to-peer to capture reputation and real-world interactions.

We formalize ideal functionalities that capture desirable security and privacy notions for proofs of personhood, including Sybil-resistance, authenticated personhood, and unlinkability across contexts. Finally, we then give efficient cryptographic constructions that realize these functionalities by combining PHCs, VRCs, and zero-knowledge proofs. Our results suggest that a scalable, Sybil-resistant, and decentralized proof-of-personhood layer can serve as a reusable trust substrate for a wide range of online economic, social, and civic applications.