International Association
for Cryptologic Research

Digital signature is a fundamental cryptographic primitive and is widely used in the real world. Unfortunately, the current digital signature standards like EC-DSA and RSA are not quantum-resistant. Among post-quantum cryptography (PQC), isogeny-based signatures preserve some advantages of elliptic curve cryptosystems, particularly offering small signature sizes. Currently, SQIsign and its variants are the most promising isogeny-based digital signature schemes. In this paper, we propose a new structure for the SQIsign family: Pentagon Isogeny-based Signature in High Dimension (referred to as $\Pi$-signHD). The new structure separates the hash of the commitment and that of the message by employing two cryptographic hash functions. This feature is desirable in reality, particularly for applications based on mobile low-power devices or for those deployed interactively over the Internet or in the cloud computing setting. This structure can be generally applicable to all the variants of SQIsign. In this work, we focus on the instance based on SQIsignHD, proposed by Dartois, Leroux, Robert and Wesolowski (Eurocrypt 2024). Compared with SQIsignHD, $\Pi$-signHD has the same signature size (even smaller for some application scenarios). For the NIST-I security level, the signature size of $\Pi$-signHD can be reduced to 519 bits, while the SQIsignHD signature takes 870 bits. Additionally, $\Pi$-signHD has an efficient online signing process, and enjoys much desirable application flexibility. In our experiments, the online signing process of $\Pi$-signHD runs in 4 ms.

The machine learning problem of extracting neural network parameters has been proposed for nearly three decades. Functionally equivalent extraction is a crucial goal for research on this problem. When the adversary has access to the raw output of neural networks, various attacks, including those presented at CRYPTO 2020 and EUROCRYPT 2024, have successfully achieved this goal. However, this goal is not achieved when neural networks operate under a hard-label setting where the raw output is inaccessible. In this paper, we propose the first attack that theoretically achieves functionally equivalent extraction under the hard-label setting, which applies to ReLU neural networks. The effectiveness of our attack is validated through practical experiments on a wide range of ReLU neural networks, including neural networks trained on two real benchmarking datasets (MNIST, CIFAR10) widely used in computer vision. For a neural network consisting of $10^5$ parameters, our attack only requires several hours on a single core.

This paper introduces a ZKP (zero-knowledge proof) based state update system, where each block contains a SNARK proof aggregated from the user generated zkVM (zero knowledge virtual machine) proofs. It enables users to generate state update proofs in their local machines, contributing to a secure, decentralized verification process. Our main contribution in this paper, the recursive proofs system, addresses scalability by recursively verifying user proofs and aggregating them in a hierarchical tree structure up to a root proof, serving as a block proof. The proposed solution advances current blockchain paradigms by offering efficient recursive verification through ZKP, enhancing security and reducing computational load.

Recent constructions of vector commitments and non-interactive zero-knowledge (NIZK) proofs from LWE implicitly solve the following /shifted multi-preimage sampling problem/: given matrices $\mathbf{A}_1, \ldots, \mathbf{A}_\ell \in \mathbb{Z}_q^{n \times m}$ and targets $\mathbf{t}_1, \ldots, \mathbf{t}_\ell \in \mathbb{Z}_q^n$, sample a shift $\mathbf{c} \in \mathbb{Z}_q^n$ and short preimages $\boldsymbol{\pi}_1, \ldots, \boldsymbol{\pi}_\ell \in \mathbb{Z}_q^m$ such that $\mathbf{A}_i \boldsymbol{\pi}_i = \mathbf{t}_i + \mathbf{c}$ for all $i \in [\ell]$. In this work, we introduce a new technique for sampling $\mathbf{A}_1, \ldots, \mathbf{A}_\ell$ together with a succinct public trapdoor for solving the multi-preimage sampling problem with respect to $\mathbf{A}_1, \ldots, \mathbf{A}_\ell$. This enables the following applications:

* We provide a dual-mode instantiation of the hidden-bits model (and by correspondence, a dual-mode NIZK proof for NP) with (1) a linear-size common reference string (CRS); (2) a transparent setup in hiding mode (which yields statistical NIZK arguments); and (3) hardness from LWE with a polynomial modulus-to-noise ratio. This improves upon the work of Waters (STOC 2024) which required a quadratic-size structured reference string (in both modes) and LWE with a super-polynomial modulus-to-noise ratio.

* We give a statistically-hiding vector commitment with transparent setup and polylogarithmic-size CRS, commitments, and openings from SIS. This simultaneously improves upon the vector commitment schemes of de Castro and Peikert (EUROCRYPT 2023) as well as Wee and Wu (EUROCRYPT 2023).

At a conceptual level, our work provides a unified view of recent lattice-based vector commitments and hidden-bits model NIZKs through the lens of the shifted multi-preimage sampling problem.

Password Authenticated Key Exchange (PAKE) allows two parties to establish a secure session key with a shared low-entropy password pw. Asymmetric PAKE (aPAKE) extends PAKE in the client-server setting, and the server only stores a password file instead of the plain password so as to provide additional security guarantee when the server is compromised. In this paper, we propose a novel generic compiler from PAKE to aPAKE in the Universal Composable (UC) framework by making use of Key Encapsulation Mechanism (KEM) and Authenticated Encryption (AE).

-- Our compiler admits efficient instantiations from lattice to yield lattice-based post-quantum secure aPAKE protocols. When instantiated with Kyber (the standardized KEM algorithm by the NIST), the performances of our compiler outperform other lattice-based compilers (Gentry et al. CRYPTO 2006) in all aspects, hence yielding the most efficient aPAKE compiler from lattice. In particular, when applying our compiler to the UC-secure PAKE schemes (Santos et al. EUROCRYPT 2023, Beguinet et al. ACNS 2023), we obtain the most efficient UC-secure aPAKE schemes from lattice. -- Moreover, the instantiation of our compiler from the tightly-secure matrix DDH (MDDH)-based KEM (Pan et al. CRYPTO 2023) can compile the tightly-secure % CDH-based PAKE scheme (Liu et al. PKC 2023) to a tightly-secure MDDH-based aPAKE, which serves as the first tightly UC-secure aPAKE scheme.

We revisit the Ligero proximity test, and its logarithmic randomness variant, in the framework of [EA23] and show a simple proof that improves the soundness error of the original logarithmic randomness construction of [DP23] by a factor of two. This note was originally given as a presentation in ZK Summit 11.

This paper presents an architecture for an OAuth 2.0-based i-voting solution using a mobile native client in a variant of the Ara´ujo-Traor´e protocol. We follow a systematic approach by identifying relevant OAuth 2.0 specifications and best practices. Having defined our framework, we identify threats applicable to our proposed methodology and detail how our design mitigates them to provide a safer i-voting process.

Digital signatures ensure authenticity and secure communication. They are used to verify the integrity and authenticity of signed documents and are widely utilized in various fields such as information technologies, finance, education, and law. They are crucial in securing servers against cyber attacks and authenticating connections between clients and servers. Additionally, encryption is used in many areas, such as secure communication, cloud, server and database security to ensure data confidentiality. Performing batch encryption, signature generation, and signature verification simultaneously and efficiently is highlighted as a beneficial approach for many systems. This work focuses on efficient batch signature generation with Dilithium, batch verifications of signatures from the same user using Crystals Dilithium (NIST's post-quantum digital signature standard) and batch encryption to a single user with Crystals Kyber (NIST's post-quantum encryption/KEM standard). One of the main operations of Dilithium and Kyber is the matrix-vector product with polynomial entries. So, the naive approach to generate/verify m signatures with Dilithium (or encrypt $m$ messages with Kyber) where m>1 is to perform $m$ such multiplications. In this paper, we propose to use efficient matrix multiplications of sizes greater than four to generate/verify m signatures with Dilithium and greater than two to encrypt $m$ messages with Kyber. To this end, batch algorithms that transform the polynomial matrix-vector multiplication in Dilithium's and Kyber's structures into polynomial matrix-matrix multiplication are designed. The batch numbers and the sizes of the matrices to be multiplied based on the number of repetitions of Dilithium's signature algorithm are determined. Also, batch versions of Dilithium verification and Kyber encryption algorithms are proposed. Moreover, many efficient matrix-matrix multiplication algorithms, such as Strassen-like multiplications and commutative matrix multiplications, are analyzed to design the best algorithms that are compatible with the specified dimensions and yield improvements. Various multiplication formulas are derived for different security levels of Dilithium signature generation, verification, and Kyber encryption. Improvements up to 28.1%, 33.3%, and 31.5% in the arithmetic complexities are observed at three different security levels of Dilithium's signature, respectively. The proposed batch Dilithium signature algorithm and the efficient multiplication algorithms are also implemented, and 34.22%, 17.40%, and 10.15% improvements on CPU cycle counts for three security levels are obtained. The multiplication formulas used for batch Dilithium signature generation are also applied for batch Dilithium verification. At three different levels of security, improvements in the arithmetic complexity are observed of up to 28.13%, 33.33%, and 31.25%. Furthermore, 49.88%, 56.60%, and 61.08% improvements on CPU cycle counts for three security levels are achieved, respectively. As a result of implementing Kyber Batch Encryption with efficient multiplication algorithms, 12.50%, 22.22%, and 28.13% improvements on arithmetic complexity, as well as 22.34%, 24.07%, and 30.83\% improvements on CPU cycle counts, are observed for three security levels.

Recently, there has been a lot of interest in improving the understanding of the practical hardness of the 3-Tensor Isomorphism (3-TI) problem, which, given two 3-tensors, asks for an isometry between the two. The current state-of-the-art for solving this problem is the algebraic algorithm of Ran et al. '23 and the graph-theoretic algorithm of Narayanan et al. '24 that have both slightly reduced the security of the signature schemes MEDS and ALTEQ, based on variants of the 3-TI problem (Matrix Code Equivalence (MCE) and Alternating Trilinear Form Equivalence (ATFE) respectively).

In this paper, we propose a new combined technique for solving the 3-TI problem. Our algorithm, as typically done in graph-based algorithms, looks for an invariant in the graphs of the isomorphic tensors that can be used to recover the secret isometry. However, contrary to usual combinatorial approaches, our approach is purely algebraic. We model the invariant as a system of non-linear equations and solve it. Using this modelling we are able to find very rare invariant objects in the graphs of the tensors — cycles of length 3 (triangles) — that exist with probability approximately $1/q$. For solving the system of non-linear equations we use Gröbner-basis techniques adapted to tri-graded polynomial rings. We analyze the algorithm theoretically, and we provide lower and upper bounds on its complexity. We further provide experimental support for our complexity claims. Finally, we describe two dedicated versions of our algorithm tailored to the specifics of the MCE and the ATFE problems.

The implications of our algorithm are improved cryptanalysis of both MEDS and ALTEQ for the cases when a triangle exists, i.e. in approximately $1/q$ of the cases. While for MEDS, we only marginally reduce the security compared to previous work, for ALTEQ our results are much more significant with at least 60 bits improvement compared to previous work for all security levels. For Level I parameters, our attack is practical, and we are able to recover the secret key in only 1501 seconds. The code is available for testing and verification of our results.

We present the formal verification of Apple’s iMessage PQ3, a highly performant, device-to-device messaging protocol offering strong security guarantees even against an adversary with quantum computing capabilities. PQ3 leverages Apple’s identity services together with a custom, post-quantum secure initialization phase and afterwards it employs a double ratchet construction in the style of Signal, extended to provide post-quantum, post-compromise security.

We present a detailed formal model of PQ3, a precise specification of its fine-grained security properties, and machine-checked security proofs using the TAMARIN prover. Particularly novel is the integration of post-quantum secure key encapsulation into the relevant protocol phases and the detailed security claims along with their complete formal analysis. Our analysis covers both key ratchets, including unbounded loops, which was believed by some to be out of scope of symbolic provers like TAMARIN (it is not!).

Multiparty computation (MPC) is an important field of cryptography that deals with protecting the privacy of data, while allowing to do computation on that data. A key part of MPC is the parties involved having correlated randomness that they can use to make the computation or the communication between themselves more efficient, while still preserving the privacy of the data. Examples of these correlations include random oblivious transfer (OT) correlations, oblivious linear-function evaluation (OLE) correlations, multiplication triples (also known as Beaver triples) and one-time truth tables. Multi-point function secret sharing (FSS) has been shown to be a great building block for pseudo-random correlation generators. The main question is how to construct fast and efficient multi-point FSS schemes. Here we propose a natural generalization of the scheme of Boyle et al 2016 using a tree structure, a pseudorandom generator and systems of linear equations. Our schemes SLAMP-FSS and SLAMPR-FSS are more efficient in the evaluation phase than other previously proposed multi-point FSS schemes while being also more flexible and being similar in other efficiency parameters.

Payment channel networks (PCNs) are a leading method to scale the transaction throughput in cryptocurrencies. Two participants can use a bidirectional payment channel for making multiple mutual payments without committing them to the blockchain. Opening a payment channel is a slow operation that involves an on-chain transaction locking a certain amount of funds. These aspects limit the number of channels that can be opened or maintained. Users may route payments through a multi-hop path and thus avoid opening and maintaining a channel for each new destination. Unlike regular networks, in PCNs capacity depends on the usage patterns and, moreover, channels may become unidirectional. Since payments often fail due to channel depletion, a protection scheme to overcome failures is of interest. We define the stopping time of a payment channel as the time at which the channel becomes depleted. We analyze the mean stopping time of a channel as well as that of a network with a set of channels and examine the stopping time of channels in particular topologies. We then propose a scheme for optimizing the capacity distribution among the channels in order to increase the minimal stopping time in the network. We conduct experiments and demonstrate the accuracy of our model and the efficiency of the proposed optimization scheme.

We present the first Key Policy Attribute-Based Encryption (KP-ABE) scheme employing isogeny-based cryptography through class group actions, specifically utilizing the Csi-FiSh instantiation and pairing groups. We introduce a new assumption, denoted Isog-DLin, which combines the isogeny and DLin assumptions. We propose the following constructions: a small universe KP-ABE and a large universe KP-ABE under the Isog-DBDH assumption, and a small universe KP-ABE under the Isog-DLin assumption. In these constructions, the master key is designed to be secure against quantum computer attacks, while the ciphertext remains secure against classical computer attacks. This dual-layered approach ensures robust security across classical and quantum computational paradigms, addressing current and potential future cryptographic challenges.

Secure join queries over encrypted database, the most expressive class of SQL queries, have attracted extensive attention recently. The state-of-the-art JXT (Jutla et al. ASIACRYPT 2022) enables join queries on encrypted relational database without pre-computing all possible joins. However, JXT can merely support join queries over two tables (in encrypted database) with some high-entropy join attributes.

In this paper, we propose an equi-join query protocol over two tables dubbed JXT+, that allows the join attributes with arbitrary names instead of JXT requiring the identical name for join attributes. JXT+ reduces the query complexity from $O(\ell_1 \cdot \ell_2)$ to $O(\ell_1)$ as compared to JXT, where $\ell_1$ and $\ell_2$ denote the numbers of matching records in two tables respectively. Furthermore, we present JXT++, the \emph{first} equi-join queries across three or more tables over encrypted database without pre-computation. Specifically, JXT++ supports joins of arbitrary attributes, i.e., all attributes (even low-entropy) can be candidates for join, while JXT requires high-entropy join attributes. In addition, JXT++ can alleviate sub-query leakage on three or more tables, which hides the leakage from the matching records of two-table join.

Finally, we implement and compare our proposed schemes with the state-of-the-art JXT. The experimental results demonstrate that both of our schemes are superior to JXT in search and storage costs. In particular, JXT+ (resp., JXT++) brings a saving of 49% (resp., 68%) in server storage cost and achieves a speedup of 51.7$\times$ (resp., 54.3$\times$) in search latency.

Event date: 14 September to 18 September 2025

Event date: 30 June to 4 July 2025
Submission deadline: 24 October 2024
Notification: 13 February 2025

Offer Description

Centre for Hardware Security at the Department of Computer Systems in Tallinn University of Technology (TalTech) invites MSc holders in Computer Science or relevant fields to apply for a PhD position in secure hardware-efficient realization of lightweight cryptography algorithms.

Project Description

Lightweight cryptography plays an important role to ensure integrity, confidentiality, and security of sensitive information on devices with limited resources, such as internet of things (IoT) and wireless sensor networks. In our project, we aim to (i) explore hardware-efficient realizations of lightweight cryptography algorithms taking into account performance, power, and area (PPA) requirements; (ii) secure these implementations against well-known attacks, such as side-channel analysis and fault injection, considering the PPA overhead; and (iii) demonstrate promising designs in an application-specific integrated circuit and embed them in a real-world IoT environment.

Requirements

Education

MSc degree in Computer Science, Electrical Engineering, or Computer Engineering

Essential Knowledge and Experience

Knowledge of hardware description languages Verilog/VHDL

Knowledge of hardware design techniques targeting high performance and low power dissipation

Experience in digital system design at RTL using Verilog/VHDL on FPGA/ASIC

Knowledge of cryptography algorithms including block ciphers and hash functions

Knowledge of hardware security including side-channel analysis and fault injection attacks

Additional Knowledge and Experience

Experience in programming with C/C++

Experience in the design of cryptography algorithms in hardware

Experience in scripting languages, such as Perl, Tcl, and bash

How to Apply

Please submit your CV with a cover letter including your interest in this position to Dr. Levent Aksoy by e-mail (levent.aksoy@taltech.ee).

Closing date for applications:

Contact: Levent Aksoy

A 2-year post-doctoral research associate position is available at the Cyber Security & Privacy Research Group, Department of Computer Science, University of York, UK, to work on a research project at the intersection of cyber security and AI.
The ideal candidate will have expertise in security and privacy and familiarity with AI concepts. Experience in cryptographic design of privacy-enhancing technologies including zero-knowledge proofs, secure multi-party computation, or differential privacy is particularly welcome.
You will be working with a multi-disciplinary team spanning 7 universities across the UK and several industrial project partners (see project website: https://phawm.org).

Closing date for applications:

Contact: Dr. Siamak Shahandashti (siamak.shahandashti@york.ac.uk) for informal enquiries.
Applications need to be formally made by 1/10/2024 at https://jobs.york.ac.uk/vacancy/research-associate-566847.html, where further information about the position can also be found.

More information: https://jobs.york.ac.uk/vacancy/research-associate-566847.html

The area of modern zero-knowledge proof systems has seen a significant rise in popularity over the last couple of years, with new techniques and optimized constructions emerging on a regular basis.

As the field matures, the aspect of implementation attacks becomes more relevant, however side-channel attacks on zero-knowledge proof systems have seen surprisingly little treatment so far. In this paper we give an overview of potential attack vectors and show that some of the underlying finite field libraries, and implementations of heavily used components like hash functions, are vulnerable w.r.t. cache attacks on CPUs.

On the positive side, we demonstrate that the computational overhead to protect against these attacks is relatively small.

The see-in-the-middle (SITM) attack combines differential cryptanalysis and the ability to observe differential patterns in the side-channel leakage traces to reveal the secret key of SPN-based ciphers. While SITM presents a fresh perspective to side-channel analysis and allows attacks on deeper cipher rounds, there are practical difficulties that come with this method. First, one must realize a visual inspection of millions of power traces. Second, there is a strong requirement to reduce noise to a minimum, achieved by averaging over 1000 traces in the original work, to see the patterns. Third, the presence of a jitter-based countermeasure greatly affects pattern identification, making the visual inspection infeasible. In this paper we aim to tackle these difficulties by using a machine learning approach denoted as DL-SITM (deep learning SITM). The fundamental idea of our approach is that, while a collision obscured by noise is imperceptible in a manual inspection, a powerful deep learning model can identify it, even when a jitter-based countermeasure is in place. As we show with a practical experiment, the proposed DL-SITM approach can distinguish the two valid differentials from over 4M differential traces with only six false positives. Extrapolating from the parameters of this experiment, we get a rough estimate of $2^{43}$ key candidates for the post-processing step of our attack, which places it easily in the practical range. At the same time, we show that even with a jitter countermeasure shifting the execution by $\pm15$ samples, the testing f1-score stays at a relatively high (0.974).