International Association
for Cryptologic Research

This work introduces a polynomial-time attack on the signature scheme Facto-DSA. We provide an implementation that breaks all proposed parameter sets, including the largest, in under one minute on a standard laptop. These results question the suitability of multivariate polynomial factorization as a foundation for robust cryptographic schemes.

Integral cryptanalysis analyzes block ciphers using input structures for which the sum of a chosen function of the output bits becomes key-independent. However, most methods still test one output expression at a time, so they can miss distinguishers that emerge only when several outputs are combined, either linearly or nonlinearly. They are also not designed to capture key-dependent integral combinations, which may hold deterministically on part of the key space. In this work, we develop Split-and-Cancel, a method that combines exact expansion in a short final part with an oracle on the preceding rounds to determine which suffix monomials can survive from the chosen structure and records them in a binary matrix. Key-independent combinations are then extracted from the left kernel of this matrix. We first apply the method in a reduced model with omitted boundary key additions, where linear dependencies in this matrix yield certified key-independent sum combinations among output bits and higher-degree output products. When the omitted boundary key is restored, the same combinations yield deterministic weak-key distinguishers. We apply the method to SIMON, SIMECK, SPECK, PRESENT, and GIFT. Our strongest deterministic results add one round to the best integral distinguishers for SIMON-32, SIMON-48, SIMON-64, SIMON-96, SIMON-128, all standard SIMECK variants, and SPECK from block sizes 32 to 128. For PRESENT and GIFT, we obtain one-round improvements for deterministic weak-key integral distinguishers. In each case, the exact weak-key class covers at least a quarter of the key space: $2^{78}$ of $2^{80}$ keys for PRESENT-80, $2^{126}$ of $2^{128}$ keys for PRESENT-128, GIFT-64 and GIFT-128. These results show that exact modeling of a short final part can reveal key-independent and weak-key integral behavior missed by single-observable searches.

Fully homomorphic encryption (FHE) enables computation on encrypted data without decryption. In TFHE, programmable bootstrapping (PBS) evaluates nonlinear functions through lookup tables (LUTs), but a direct multivariate LUT over a $t$-ary plaintext space has size $t^\ell$. This paper studies LUT compression for multivariate functional bootstrapping via variable separation and additive inner representations.

We first apply this approach to non-negative integer division with remainder. For a dividend $m$, a divisor $d$, and $h=\lfloor m/d\rfloor$, we use a logarithmic transformation to decompose bivariate division into two univariate logarithmic PBS calls, one homomorphic subtraction, and one outer exponential PBS call. To handle integer plaintexts, we introduce a rounded logarithmic function $\operatorname{clog}_{B,M}$ and give a sufficient condition on $M$ for exact quotient recovery. The resulting homomorphic division-with-remainder algorithm achieves $\widetilde{O}(1)$ equivalent blind-rotation complexity under theoretically optimal parameters, and also yields frameworks for modular reduction and truncated division.

We further prove that every finite function $f:[t]^\ell\to[t]$ can be written as $f(x_1,\ldots,x_\ell)=q\left(\sum_{i=1}^{\ell}p_i(x_i)\right)$, and search for small-span representations using simulated annealing with reheating. Experiments show a 3.6x speedup for division with remainder at $t=64$, and a 1.9x speedup for the Hamming-weight interval function, compared with estimates based on [BBR26].

The threat of large-scale quantum computers to classical public-key cryptography has motivated the development of post-quantum cryptographic schemes. Among these, lattice-based constructions have become the mainstream choice in the ongoing NIST standardization process. The security of these schemes typically relies on the hardness of the LWE problem, and the dual-sieve-FFT attack is widely recognized as one of the most effective approaches against it. Recent improvements by MATZOV and Carrier et al. have significantly advanced its efficiency. In this paper, we propose a new variant of the dual-sieve-FFT attack that integrates modulus switching and lossy source coding. We provide a theoretical analysis of the integrated approach and show that the enumeration size in the FFT step can be reduced from $q^{n_\text{fft}}$ to $p^{k_\text{fft}}$ (with $p

As privacy concerns rise, numerous laws require machine learning-based applications to comply with stringent privacy regulations. While Homomorphic Encryption (HE) allows computation directly on encrypted data, existing HE-based inference solutions suffer from significant computational and memory overhead for both single and multiple samples. Additionally, current methods require many rotation keys, which limits their practicality in a broader range of scenarios.

To address these challenges, we propose channel-interleaved packing (CHIP) to embed three-dimensional (3-D) data into 2-D ciphertexts, enabling 3-D HE convolution to be performed as a 2-D HE convolution combined with channel aggregations via ciphertext rotations. To further improve the performance of CHIP-based convolution, we introduce an efficient 2-D convolution that halves the number of HE multiplications. For computationally intensive inference tasks, we employ partial-kernel and mini-batch strategies that iteratively process sliced kernels and subsets of samples, aggregating the results to produce the final output.

Experimental results demonstrate the superior efficiency of our method compared to the state-of-the-art HE-based approaches by Lee et al. (ICML'22) and Cheon et al. (IEEE TDSC'24) in both single-sample and multi-sample scenarios. Using ResNet18, VGG11, and VGG16 with a batch size of 64, our solution achieves speedups of up to 4.7$\times$. When processing a single test sample, the speedup increases to 60$\times$. Moreover, our method requires only 29 rotation keys for evaluation, which is at least 35\% fewer than previous works, resulting in an overall memory reduction of up to 45\%. Code is available at: \url{https://github.com/whcjimmy/chip}.

This work revisits a natural paradigm for constructing public-key encryption, whereby the public key is an obfuscated block cipher in encryption mode. We show that if the block cipher is a permutable pseudorandom permutation [Shmueli–Zhandry, Crypto ’25] and the obfuscator is indistinguishability-secure, then the following holds.

1. Applying the obfuscated cipher directly to the message and a short random nonce, without any additional structure or consistency checks, suffices for CCA2 security. 2. Augmenting the scheme with the capability to generate obfuscated decrypt-then-apply-$f$ circuits (for any given function $f$), yields a *functional encryption* scheme that is *simulation-secure against adaptive chosen-ciphertext attacks*. 3. For any length-preserving function $g$, augmenting the public key with an obfuscated decrypt-apply-$g$-reencrypt circuit allows anyone to homomorphically apply $g$ to encrypted data, for an unbounded number of times, while preserving semantic security. (This relies on subexponential security.)

We also show that, under the split-circuit pseudorandomness (SCP) assumption of [Canetti–Chamon–Mucciolo–Ruckenstein, TCC ’24], random reversible circuits form a permutable pseudorandom permutation family. This points to obfuscated random reversible circuits as a potential alternative avenue to public-key encryption with strong security and rich functionality.

With growing concerns over data privacy, private nearest neighbors search (PNNS) attracts increasing research attention. Existing PNNS follow two main approaches: i) interactive PNNS based on secure multi-party computation protocols that leverage index structures to achieve sublinear complexity, and ii) non-interactive PNNS utilizing fully homomorphic encryption to minimize communication bandwid that the cost of superlinear computational complexity. To address the communication-computation dilemma, we propose HANNS, a non-interactive PNNS protocol with a sublinear number of encrypted comparisons. Our key observation is that, while the full-table scan is inevitable under the non-interactive setting, the number of costly encrypted comparisons can be significantly reduced. Specifically, we develop a cluster ordering scheme over FHE that leverages a segmented rigid transformation to obliviously identify candidate clusters with only a sublinear number of homomorphic comparisons. Furthermore, we introduce a homomorphic product quantization (PQ) scheme that enables coarse search and reranking over PQ-encoded vectors, which significantly reduces the computational and storage overheads. In the experiment, we show that HANNS achieves 41x to 277x speedup and a storage reduction of 12x to 31.7x compared to the most recent non-interactive schemes, while reducing communication by 1,258x to 80,536x and achieving a speedup of 8x to 119x over interactive schemes in low-bandwidth scenarios.

The objective of this work is to investigate methods for improving the self-tuning mechanism of ring oscillator (RO) based True Random Number Generators (TRNGs). It also examines the challenges involved in achieving a reliable and stable design over long-term operation. Furthermore, this work analyzes potential approaches to address these challenges and validates their effectiveness using the NIST statistical test suite.

Blind side-channel analysis (BSCA) can infer keys without known inputs or outputs, but practical use still needs an upstream step that locates repeated computation and candidate points of interest in an unlabeled trace. We address this trace-only structuring problem with a two-stage method that uses only the per-sample mean and standard deviation, without algorithm labels or metadata. Stage1 estimates a repetition scale, start phase, anchor-supported stable core, and period candidates from rank-combined self-similarity. Stage2 stacks the stable core into a representative repetition and partitions it into relative high- and low-score segments. On 16 block cipher implementations across STM32F303 and XMEGA, the method forms consistent repetition windows in most cases. Post-hoc source and assembly comparison separates exact or edge-inclusive count matches from grouped, microperiod, and ambiguous hierarchy relations, while Top-5 candidates often retain body-related hierarchy. In a representative AES/XMEGA case, the trace-only high-score segments cover the strongest S-box CPA hotspots, indicating that the produced coordinates can prioritize, rather than determine, candidate regions for later CPA or BSCA.

Blockchain-based cryptocurrencies give rise to a plenitude of advanced applications (such as cross-currency transfers or privacy-preserving payments) through blockchain protocols - cryptographic protocols that orchestrate the processing of financial transactions on the blockchain. To enable a modular design and to enhance reusability across different cryptocurrencies, many blockchain protocols are built upon adaptor signatures (AS), a well-studied cryptographic building block, which is natively supported by most digital signature schemes used for authorizing cryptocurrency transactions. An inherent limitation of AS-based blockchain protocols is the known impossibility to realize AS for unique signature schemes, such as BLS signatures. As a consequence, existing AS-based protocols cannot be executed on cryptocurrencies that base transaction authorization on BLS signatures (such as the Chia Network).

For such cryptocurrencies, instead, new custom blockchain protocols need to be created, as recently done for the case of coin mixing (S&P'24) or atomic swaps between two cryptocurrencies with BLS-based transaction authorization (ESORICS'24). To avoid such complex and error-prone redesigns, in this work, we develop a novel notion of AS called Two-Party Asymmetric-Input Solitary-Output Adaptor Signature (2P-AISO-AS) that sidesteps the known impossibility result and that can be realized from both randomized (i.e., plain) and unique signature schemes. We provide efficient instantiations of 2P-AISO-AS from BLS and show that we can obtain performant, BLS-compatible blockchain protocols by replacing AS with 2P-AISO-AS in known AS-based protocols, including zero-knowledge contingent payments, atomic swaps, and coin mixing.

Design of hash functions and pseudo-random permutations over Galois extensions of $\mathbb Z_q$ for prime powers $q$ has recently gained some interest in relation to recent directions in advanced cryptography, such as multiparty computation and zero-knowledge protocol design. Thus investigating optimality of cryptographic properties of S-boxes defined by polynomials over Galois rings is of interest. Of particular interest is the differential uniformity of such functions. To our knowledge, there are very few results on the differential uniformity for polynomials over Galois rings $\mathrm{GR}(p^k,m)$ when $k,m\geq 2$. Motivated by designing secure hash functions and block ciphers over Galois rings, a main contribution of this paper is an investigation into the differential properties of polynomials over Galois rings. Finally, we provide a classification of APN permutations in $\mathrm{GR}(4,2)$ up to affine and CCZ-equivalence.

Boolean functions with additional structure play an important role in symmetric cryptography, both for achieving strong cryptographic properties and for enabling efficient implementations. Recent works on homomorphic-friendly symmetric primitives, especially in the context of Hybrid Homomorphic Encryption, highlighted the interest of Boolean functions whose evaluation can be decomposed according to structured partitions of the Boolean cube. A classical example is given by Hamming-weight decompositions, which underlie symmetric and weightwise degree-d Boolean functions. In this work, we generalize this viewpoint by replacing the Hamming weight with a general integer linear form. Given a vector v in Z^n, we partition the Boolean cube (F_2)^n by grouping the Boolean vectors x in (F_2)^n according to the value of into so-called v-slices, and study functions that have bounded degree on each of them. We study how many such slices are needed to describe a given function, and provide bounds and structural properties for the partitions induced by integer vectors. We also show how this representation leads to a homomorphic evaluation strategy in a GSW-like setting, together with noise estimates for the resulting ciphertexts. Finally, we generalize several symmetric and weightwise degree-d Boolean functions using different vector families, and experimentally evaluate their algebraic degree, algebraic immunity, and nonlinearity. The results show that direct generalizations of symmetric functions often lose cryptographic strength, while generalized weightwise degree-d constructions lead to richer and more promising behavior.

In next-generation networks, communication systems will no longer be limited to data transmission and will be expected to acquire awareness of the surrounding environment. This leads to the concept of integrated sensing and communication (ISAC), where the same wireless infrastructure is used for both communication and environmental sensing. Thus, ISAC enables the system to transmit information efficiently and observe and interpret channel variations and user behavior. Motivated by this capability, this work focuses on detecting an active attacker in an urban environment scenario, where the attacker intentionally manipulates beamforming directions to increase interference and mislead the transmitter into allocating the main lobe of beam toward itself instead of legitimate users. We apply game-theoretic approaches to model the interaction between legitimate users and the attacker, and integrate the resulting utility-based formulation into a reinforcement learning (RL) framework. Simulation results demonstrate that the proposed method effectively addresses security challenges in dynamic 6G ISAC systems.

In zero-knowledge machine learning (zkML), the dominant cost is generating the proof, not running the model, and it concentrates in the nonlinearities a transformer must evaluate inside the proof system. It is tempting to exploit a nonlinearity's mathematical structure (low degree, parity, or kernel form) to prove it more cheaply. We show this hope is misplaced for the dominant cost: in a Shout-style (one-hot) lookup argument the per-lookup proving work is a function of the access pattern alone, never of the table values, so function structure has zero leverage on it. This is a separation principle; structure can cheapen only a secondary, once-per-proof table term. That table term stays subordinate as models get deeper because the only data-dependent amplifier of per-layer error in a pre-LN transformer is the LayerNorm gain 1/σ: a σ-floor on typical inputs lets a single fixed proving precision suffice at every depth, keeping proof cost near-linear in the number of layers. We measure this depth-to-cost scaling on two independent proving systems (EZKL/halo2 and Jolt Atlas), and turn the one dial the separation leaves open, the committed address width, into a bit-exact, upstreamed reduction in prover time.

Decision trees are widely used in machine learning due to their simplicity, efficiency, and interpretability. Numerous private decision tree evaluation (PDTE) protocols based on secure multi-party computation (MPC) have been proposed to protect sensitive data during evaluation. However, existing MPC-based PDTE protocols primarily focus on the two or three-party setting. Moreover, their core building block, secure threshold comparison, typically incurs logarithmic-round communication and dominates the online cost of tree evaluation. These limitations motivate the design of scalable and efficient secure comparison protocols for large-scale PDTE. In this paper, we propose a scalable constant round secure comparison protocol with Shamir secret sharing in the honest-majority setting. Concretely, inspired by Falcon, we leverage random shuffling to achieve zero detection with constant-round communication. Furthermore, we reduce random shuffle to random shift, thereby significantly decreasing the offline communication overhead. Besides, we reformulate feature selection and path evaluation in PDTE as PLUT functionalities and integrate them with our scalable comparison protocol to achieve scalable PDTE. Finally, we extend the above Shamir secret sharing-based protocols to the packed secret sharing variants and further improve their online communication efficiency. We instantiate these protocols as a framework SC-DT and report their improved performance: i) For secure comparison, we achieve a speedup of $1.7-2.3\times$ and reduce communication by $1.7-2.5\times$ in the online phase compared with Helix (Cryptology ePrint’2025). ii) For PDTE, our protocol achieves up to a $9\times$ speedup and reduces online communication by $1.5\times$ in the online phase compared with Mostree (ACSAC’2023). iii) For large-scale decision tree evaluation tasks, SC-DT evaluates a random forest consisting of 100 trees and 85100 nodes in a 21-party WAN setting, achieving an amortized latency of approximately 300 ms per tree.

Zero-knowledge proof systems are increasingly relying on the Sumcheck protocol to avoid the FFT-heavy structure of earlier SNARK designs. Sumcheck is well suited for GPU acceleration; it consists of sequential rounds where each round performs regular, parallelizable operations over large multilinear evaluation tables. The focus is on how to organize this work across rounds: intuitively, the active polynomial state should remain close to the device that processes it, the CPU-GPU boundary should only expose values that are needed to transition, and various cryptographic settings should be kept stable.

This paper presents Chimera, a GPU-CPU framework for accelerating Sumcheck in Spartan-style SNARK provers. Chimera uses a hybrid execution model: large polynomial evaluation and folding work runs on the GPU, active polynomial state remains resident on GPU across profitable rounds, compact round messages return to Spartan's host transcript, and small domains fall back to CPU execution. Chimera also specializes the wrappers around Spartan's small round-polynomial commitments and proof objects, and introduces a memory-aware chunking path.

On BN254 Spartan R1CS instances, Chimera demonstrates a \(7.96\times\) improvement of the committed-Sumcheck region at \(N=2^{17}\), relative to clean Spartan. Across full Spartan proving runs from \(2^{12}\) to \(2^{27}\) constraints, Chimera improves end-to-end prover time for all measured sizes, reaching \(1.27\times\)-\(1.64\times\) speedup for sizes \(2^{24}\)-\(2^{27}\). Ablation studies show that Chimera's gains come from choosing the right execution boundary rather than from any single optimization. The GPU handles the large, regular Sumcheck work, while Spartan keeps the protocol state needed for transcript and verifier compatibility. This reduces movement of polynomial data without disrupting the proof system. The remaining gap between Sumcheck-region and end-to-end speedup shows that, after Sumcheck is accelerated, polynomial commitment and proof-wrapper costs become the next bottleneck.

Modern hardware security heavily relies on the assumption that pre-synthesis algorithmic protections will survive the physical fabrication pipeline. However, untrusted third-party Electronic Design Automation (EDA) toolchains often apply aggressive structural optimizations that can silently compromise perfectly symmetric designs, introducing critical data-dependent power side-channel vulnerabilities. Existing pre-silicon verification methodologies require exposing highly sensitive, proprietary gate-level intellectual property (IP) to external auditors to verify structural security. In this paper, we introduce a novel Zero-Knowledge Hardware Auditor, an end-to-end framework that provides mathematical guarantees of physical data-obliviousness without revealing the underlying circuit netlist. By translating synthesized gate-level topologies into a custom Side-Channel Intermediate Language (SCIL), our architecture maps physical dynamic switching activity into arithmetic constraints executable within a Halo2 zero-knowledge virtual machine (zkVM). This enables the first implementation of a zero-knowledge Bounded Toggle Assessment (ZK-BTA), a deterministic structural counterpart to classical Test Vector Leakage Assessment. Experimental evaluations across standard cryptographic primitives and ISCAS-85 benchmarks demonstrate that the framework successfully identifies inherently leaky logic and captures EDA-induced asymmetries, such as a 13% leakage rate introduced into a theoretically secure Montgomery Ladder, while proving the structural integrity of Dual-Rail oblivious logical topologies. Furthermore, the asymmetric zk-SNARK architecture ensures scalable component-level auditing, yielding a succinct cryptographic proof of physical security that can be publicly verified in under 0.08 seconds.

I am looking to hire exceptional postdoctoral researchers to join my research group (currently a singleton, but part of CISPA's larger research area on Algorithmic Foundations and Cryptography, "https://cispa.de/en/research/research-areas/algorithmic-foundations-and-cryptography").

Research topic should align with my research ("https://pierremeyercs.github.io/") (e.g. Theory of Cryptography and Secure Multiparty Computation).

General information about being a PostDoc at CISPA is available here: "https://career.cispa.de/jobs/postdoc-8".

Closing date for applications:

Contact: Pierre Meyer

Event date: 8 November 2026
Submission deadline: 1 August 2026
Notification: 1 September 2026

We present key-recovery attacks on the constructions of TALUS (Kao and Chang), a threshold ML-DSA (FIPS 204) construction available on arXiv and scheduled for presentation at the NIST Threshold Call Preview Talks Round 2 (TCPT-2, https://csrc.nist.gov/events/2026/tcpt).

For TALUS-MPC, which is claimed EUF-CMA secure against an adversary corrupting up to $T − 1$ parties, we show the claim is false via two independent attacks, both exploiting the same root cause. TALUS-MPC uses Feldman commitments that apply the public matrix A to secret values: key shares of $s_1$ during key generation, and contributions to the nonce $y$ during signing. Since A is left-invertible in every ML-DSA parameter set, these images are invertible by Gaussian elimination, with no lattice problem to solve. A passive observer recovers all key shares of $s_1$ directly from the key-generation broadcast, and independently recovers the aggregate nonce y from the signing broadcast, which then yields $s_1 = c^{−1} \cdot (z − y)$ from a single signature.

For TALUS-TEE and TALUS-MPC, we identify a persisting flaw: the rejection-sampling check that protects the error term $s_2$ in standard ML-DSA has been removed. Each signature leaks a noisy linear equation in $s_2$; applying least-squares recovery over the cyclotomic ring - an instance of LWE without modular reduction - recovers the full secret from a few hundred million signatures. The sample counts we derive are not optimized and we believe exploiting the bounded noise structure and lattice-reduction techniques would reduce them significantly, but we focus on establishing the structural flaw.