International Association
for Cryptologic Research

We construct perfect zero-knowledge probabilistically checkable proofs (PZK-PCPs) for every language in #P. This is the first construction of a PZK-PCP for any language outside BPP. Furthermore, unlike previous constructions of (statistical) zero-knowledge PCPs, our construction simultaneously achieves non-adaptivity and zero knowledge against arbitrary (adaptive) polynomial-time malicious verifiers.

Our construction consists of a novel masked sumcheck PCP, which uses the combinatorial nullstellensatz to obtain antisymmetric structure within the hypercube and randomness outside of it. To prove zero knowledge, we introduce the notion of locally simulatable encodings: randomised encodings in which every local view of the encoding can be efficiently sampled given a local view of the message. We show that the code arising from the sumcheck protocol (the Reed--Muller code augmented with subcube sums) admits a locally simulatable encoding. This reduces the algebraic problem of simulating our masked sumcheck to a combinatorial property of antisymmetric functions.

Banks publish daily a list of available securities/assets (axe list) to selected clients to help them effectively locate Long (buy) or Short (sell) trades at reduced financing rates. This reduces costs for the bank, as the list aggregates the bank's internal firm inventory per asset for all clients of long as well as short trades. However, this is somewhat problematic: (1) the bank's inventory is revealed; (2) trades of clients who contribute to the aggregated list, particularly those deemed large, are revealed to other clients. Clients conducting sizable trades with the bank and possessing a portion of the aggregated asset exceeding $50\%$ are considered to be concentrated clients. This could potentially reveal a trading concentrated client's activity to their competitors, thus providing an unfair advantage over the market.

Atlas-X Axe Obfuscation, powered by new differential private methods, enables a bank to obfuscate its published axe list on a daily basis while under continual observation, thus maintaining an acceptable inventory Profit and Loss (P\&L) cost pertaining to the noisy obfuscated axe list while reducing the clients' trading activity leakage. Our main differential private innovation is a differential private aggregator for streams (time series data) of both positive and negative integers under continual observation.

For the last two years, Atlas-X system has been live in production across three major regions—USA, Europe, and Asia—at J.P. Morgan, a major financial institution, facilitating significant profitability. To our knowledge, it is the first differential privacy solution to be deployed in the financial sector. We also report benchmarks of our algorithm based on (anonymous) real and synthetic data to showcase the quality of our obfuscation and its success in production.

Classifying images has become a straightforward and accessible task, thanks to the advent of Deep Neural Networks. Nevertheless, not much attention is given to the privacy concerns associated with sensitive data contained in images. In this study, we propose a solution to this issue by exploring an intersection between Machine Learning and cryptography. In particular, Fully Homomorphic Encryption (FHE) emerges as a promising solution, as it enables computations to be performed on encrypted data. We, therefore, propose a Residual Network implementation based on FHE which allows the classification of encrypted images, ensuring that only the user can see the result. We suggest a circuit which reduces the memory requirements by more than 85% compared to the most recent works, while maintaining a high level of accuracy and a short computational time. We implement the circuit using the well-known CKKS scheme, which enables approximate encrypted computations. We evaluate the results from three perspectives: memory requirements, computational time and calculations precision. We demonstrate that it is possible to evaluate an encrypted ResNet20 in less than five minutes on a laptop using approximately 15GB of memory, achieving an accuracy of 91.67% on the CIFAR-10 dataset, which is almost equivalent to the accuracy of the plain model (92.60%).

Given two elliptic curves and the degree of an isogeny between them, finding the isogeny is believed to be a difficult problem---upon which rests the security of nearly any isogeny-based scheme. If, however, to the data above we add information about the behavior of the isogeny on a large enough subgroup, the problem can become easy, as recent cryptanalyses on SIDH have shown. Between the restriction of the isogeny to a full $N$-torsion subgroup and no ''torsion information'' at all lies a spectrum of interesting intermediate problems, raising the question of how easy or hard each of them is. Here we explore modular isogeny problems where the torsion information is masked by the action of a group of $2\times 2$ matrices. We give reductions between these problems, classify them by their difficulty, and link them to security assumptions found in the literature.

In this paper, we describe new quantum generic attacks on 6 rounds balanced Feistel networks with internal functions or internal permutations. In order to obtain our new quantum attacks, we revisit a result of Childs and Eisenberg that extends Ambainis' collision finding algorithm to the subset finding problem. In more details, we continue their work by carefully analyzing the time complexity of their algorithm. We also use four points structures attacks instead of two points structures attacks that leads to a complexity of $\mathcal{O}(2^{8n/5})$ instead of $\mathcal{O}(2^{2n})$. Moreover, we have also found a classical (i.e. non quantum) improved attack on $6$ rounds with internal permutations. The complexity here will be in $\mathcal{O}(2^{2n})$ instead of $\mathcal{O}(2^{3n})$ previously known.

Lattice-based cryptography has emerged as a promising new candidate to build cryptographic primitives. It offers resilience against quantum attacks, enables fully homomorphic encryption, and relies on robust theoretical foundations. Zero-knowledge proofs (ZKPs) are an essential primitive for various privacy-preserving applications. For example, anonymous credentials, group signatures, and verifiable oblivious pseudorandom functions all require ZKPs. Currently, the majority of ZKP systems are based on elliptic curves, which are susceptible to attacks from quantum computers. This project presents the first implementation of Lantern, a state-of-the-art lattice-based ZKP system that can create compact proofs, which are a few dozen kilobytes large, for basic statements. We thoroughly explain the theory behind the scheme and give a full implementation in a Jupyter Notebook using SageMath to make Lantern more accessible to researchers. Our interactive implementation allows users to fully understand the scheme and its building blocks, providing a valuable resource to understand both ZKPs and lattice cryptography. Albeit not optimized for performance, this implementation allows us to construct a Module-LWE secret proof in 35s on a consumer laptop. Through our contributions, we aim to advance the understanding and practical utilization of lattice-based ZKP systems, particularly emphasizing accessibility for the broader research community.

We explore Zero-Knowledge proofs (ZKP) of statements expressed as programs written in high-level languages, e.g., C or assembly. At the core of executing such programs in ZK is the repeated evaluation of a CPU step, achieved by branching over the CPU’s instruction set. This approach is general and covers traversal-execution of a program’s control flow graph (CFG): here CPU instructions are straight-line program fragments (of various sizes) associated with the CFG nodes. This highlights the usefulness of ZK CPUs with a large number of instructions of varying sizes.

We formalize and design an efficient tight ZK CPU, where the cost (both computation and communication, for each party) of each step depends only on the instruction taken. This qualitatively improves over state-of-the-art, where cost scales with the size of the largest CPU instruction (largest CFG node).

Our technique is formalized in the standard commit-and-prove paradigm, so our results are compatible with a variety of (interactive and non-interactive) general-purpose ZK.

We implemented an interactive tight arithmetic (over $\mathbb{F}_{2^{61}-1}$) ZK CPU based on Vector Oblivious Linear Evaluation (VOLE) and compared it to the state-of-the-art non-tight VOLE-based ZK CPU Batchman (Yang et al. CCS’23). In our experiments, under the same hardware configuration, we achieve comparable performance when instructions are of the same size and a $5$-$18×$ improvement when instructions are of varied size. Our VOLE-based ZK CPU can execute $100$K (resp. $450$K) multiplication gates per second in a WAN-like (resp. LAN-like) setting. It requires ≤ $102$ Bytes per multiplication gate. Our basic building block, ZK Unbalanced Read-Only Memory (ZK UROM), may be of an independent interest.

Event date: 19 December to 20 December 2024
Submission deadline: 9 July 2024
Notification: 13 August 2024

Event date: 25 September to 27 September 2024
Submission deadline: 22 April 2024
Notification: 9 July 2024

Event date: 24 September to 27 September 2024
Submission deadline: 14 April 2024
Notification: 17 June 2024

We have several open PhD internship positions in Bell Labs (Belgium) for PhD students or Postdocs.

At Bell Labs, the research arm of Nokia, we are currently designing and building systems that offer (1) computational integrity, (2) confidentiality, and (3) low-latency operations.

Internship Details:

As an intern in our lab, you'll have the opportunity to contribute to applied research in one of these areas, including:

Zero-Knowledge Proofs: Dive into topics like SNARKs, STARKs, and MPC-in-the-Head to enhance computational integrity. Computing on Encrypted Data: Explore homomorphic encryption (FHE) and secure multiparty computation (MPC) to address confidentiality challenges.
Acceleration: Investigate optimized implementations, software architecture, novel ZKP/FHE/MPC circuits, systems and friendly primitives.

Any other relevant subjects in this area are also welcome, such as zkML, FHE+ML, verifiable FHE, applications of MPC, and beyond.


Candidate Profile:

• You are currently doing a PhD or PostDoc
• Some familiarity with one of the areas: FHE, MPC or ZKP
• Both applied and theoretical researchers are welcome

What we offer:

• Fully funded internship with benefits (based on Belgian income standards)
• Internship any time from now until the end of 2024
• Possibility to visit local university crypto groups (e.g. COSIC KU Leuven)
• A wonderful desk with a view of the Zoo of Antwerp (elephants and bisons visible)
• Having access to the best beers and chocolates in the world

Closing date for applications:

Contact: Emad Heydari Beni (emad.heydari_beni@nokia-bell-labs.com)

At the Department of Software Systems and Cybersecurity (SSC) at Monash, we have several openings for PhD positions. The topics of interest are post-quantum cryptography (based on lattices and/or hash), their applications, and their secure and efficient software and hardware implementations.

• Amongst the benefits:
  • We provide highly competitive scholarships opportunities to collaborate with leading academic and industry experts in the above-mentioned areas.
  • There will be opportunities to participate in (inter)nationally funded projects.
  • We have a highly collaborative and friendly research environment.
  • You will have an opportunity to live/study in one of the most liveable and safest cities in the world.

The positions will be filled as soon as suitable candidates are found.

• Entry requirements include:
  • Some mathematical and cryptography backgrounds.
  • Some knowledge/experience in coding (for example, Python, C/C++, and/or SageMath) is a plus.
  • Must have completed (or be about to complete within the next 6 months) a significant research component either as part of their undergraduate (honours) degree or masters degree.
  • Should have excellent verbal and written communication skills in English.

How to apply. Please fill out the following form (also clickable from the advertisement title): https://docs.google.com/forms/d/e/1FAIpQLSetFZLvDNug5SzzE-iH97P9TGzFGkZB-ly_EBGOrAYe3zUYBw/viewform?usp=sf_link

Closing date for applications:

Contact: Amin Sakzad (amin.sakzad@monash.edu)

More information: https://www.monash.edu/it/ssc/cybersecurity/people

Private messaging platforms provide strong protection against platform eavesdropping, but malicious users can use privacy as cover for spreading abuse and misinformation. In an attempt to identify the sources of misinformation on private platforms, researchers have proposed mechanisms to trace back the source of a user-reported message (CCS '19,'21). Unfortunately, the threat model considered by initial proposals allowed a single user to compromise the privacy of another user whose legitimate content the reporting user did not like. More recent work has attempted to mitigate this side effect by requiring a threshold number of users to report a message before its origins can be identified (NDSS '22). However, the state of the art scheme requires the introduction of new probabilistic data structures and only achieves a "fuzzy" threshold guarantee. Moreover, false positives, where the source of an unreported message is identified, are possible.

This paper introduces a new threshold source tracking technique that allows a private messaging platform, with the cooperation of a third-party moderator, to operate a threshold reporting scheme with exact thresholds and no false positives. Unlike prior work, our techniques require no modification of the message delivery process for a standard source tracking scheme, affecting only the abuse reporting procedure, and do not require tuning of probabilistic data structures.

Quantum Fourier Transformation (QFT) needs to construct the rotation gates with extremely tiny angles. Since it is impossible to physically manipulate such tiny angles (corresponding to extremely weak energies), those gates should be replaced by some scaled and controllable gates. The version of QFT is called banded QFT (BQFT), and can be mathematically specified by Kronecker product and binary fraction. But the systemic errors of BQFT has never been heuristically estimated. In this paper, we generate the programming code for BQFT and argue that its systemic errors are not negligible, which means the physical implementation of QFT with a huge transform size is still a challenge. To the best of our knowledge, it is the first time to obtain the result.

A function secret sharing (FSS) (Boyle et al., Eurocrypt 2015) is a cryptographic primitive that enables additive secret sharing of functions from a given function family $\mathcal{F}$. FSS supports a wide range of cryptographic applications, including private information retrieval (PIR), anonymous messaging systems, private set intersection and more. Formally, given positive integers $r \geq 2$ and $t < r$, and a class $\mathcal{F}$ of functions $f: [n] \to \mathbb{G}$ for an Abelian group $\mathbb{G}$, an $r$-party $t$-private FSS scheme for $\mathcal{F}$ allows a dealer to split each $f \in \mathcal{F}$ into $r$ function shares $f_1, \ldots, f_r$ among $r$ servers. Shares have the property that $f = f_1 + \cdots + f_r$ and functions are indistinguishable for any coalition of up to $t$ servers. FSS for point function $f_{\alpha_1,\ldots,\alpha_l,\beta_1,\ldots,\beta_l}$ for different $\alpha$ and $l
Most existing FSS schemes are based on the existence of one-way functions or pseudo-random generators, and as a result, hiding of function $f$ holds only against computationally bounded adversaries. Protocols employing them as building blocks are computationally secure. Several exceptions mostly focus on DPF for four, eight or $d(t+1)$ servers for positive integer $d$, and none of them provide verifiability.

In this paper, we propose DPF for $d(t+l-1)+1$ servers, where $d$ is a positive integer, offering a better key size compared to the previously proposed DPF for $d(t+1)$ servers and DCF for $dt+1$ servers, also for positive integer $d$. We introduce their verifiable extension in which any set of servers holding $t$ keys cannot persuade us to accept the wrong value of the function. This verifiability notion differs from existing verifiable FSS schemes in the sense that we verify not only the belonging of the function to class $\mathcal{F}$ but also the correctness of computation results. Our schemes provide a secret key size $O(n^{1/d}\cdot s\log(p))$ for DPF and $O(n^{1/d}\cdot s\log(p))$ for DCF, where $p^s$ is the size of group $\mathbb{G}$.

Targeted Denial-of-Service (DoS) attacks have been a practical concern for permissionless blockchains. Potential solutions, such as random sampling, are adopted by blockchains. However, the associated security guarantees have only been informally discussed in prior work. This is due to the fact that existing adversary models are either not fully capturing this attack or giving up certain design choices (as in the sleepy model or asynchronous network model), or too strong to be practical (as in the mobile Byzantine adversary model).

This paper provides theoretical foundations and desired properties for consensus protocols that resist against targeted DoS attacks. In particular, we define the Mobile Crash Adaptive Byzantine (MCAB) model to capture such an attack. In addition, we identify and formalize two properties for consensus protocols under the MCAB model, and analyze their trade-offs. As case studies, we prove that Ouroboros Praos and Algorand are secure in our MCAB model, giving the first formal proofs supporting their security guarantee against targeted DoS attacks, which were previously only informally discussed. We also illustrate an application of our properties to secure a streamlined BFT protocol, chained Hotstuff, against targeted DoS attacks.

In this work we demonstrate for the first time that a full FHE bootstrapping operation can be proven using a SNARK in practice. We do so by designing an arithmetic circuit for the bootstrapping operation and prove it using plonky2. We are able to prove the circuit on an AWS C6i.metal instance in about 20 minutes. Proof size is about 200kB and verification takes less than 10ms. As the basis of our bootstrapping operation we use TFHE's programmable bootstrapping and modify it in a few places to more efficiently represent it as an arithmetic circuit (while maintaining full functionality and security). In order to achieve our results in a memory-efficient way, we take advantage of the structure of the computation and plonky2's ability to efficiently prove its own verification circuit to implement a recursion-based IVC scheme.

An Oblivious Pseudo-Random Function (OPRF) is a two-party protocol for jointly evaluating a Pseudo-Random Function (PRF), where a user has an input x and a server has an input k. At the end of the protocol, the user learns the evaluation of the PRF using key k at the value x, while the server learns nothing about the user's input or output.

OPRFs are a prime tool for building secure authentication and key exchange from passwords, private set intersection, private information retrieval, and many other privacy-preserving systems. While classical OPRFs run as fast as a TLS Handshake, current *quantum-safe* OPRF candidates are still practically inefficient.

In this paper, we propose a framework for constructing OPRFs from post-quantum multi-party computation. The framework captures a family of so-called "2Hash PRFs", which sandwich a function evaluation in between two hashes. The core of our framework is a compiler that yields an OPRF from a secure evaluation of any function that is key-collision resistant and one-more unpredictable. We instantiate this compiler by providing such functions built from Legendre symbols, and from AES encryption. We then give a case-tailored protocol for securely evaluating our Legendre-based function, built from oblivious transfer (OT) and zero-knowledge proofs (ZKP). Instantiated with lattice-based OT and ZKPs, we obtain a quantum-safe OPRF that completes in 0.57 seconds, with less than 1MB of communication.

$n$-out-of-$n$ distributed signatures are a special type of threshold $t$-out-of-$n$ signatures. They are created by a group of $n$ signers, each holding a share of the secret key, in a collaborative way. This kind of signatures has been studied intensively in recent years, motivated by different applications such as reducing the risk of compromising secret keys in cryptocurrencies. Towards maintaining security in the presence of quantum adversaries, Damgård et al. (J Cryptol 35(2), 2022) proposed lattice-based constructions of $n$-out-of-$n$ distributed signatures and multi-signatures following the Fiat-Shamir with aborts paradigm (ASIACRYPT 2009). Due to the inherent issue of aborts, the protocols either require to increase their parameters by a factor of $n$, or they suffer from a large number of restarts that grows with $n$. This has a significant impact on their efficiency, even if $n$ is small. Moreover, the protocols use trapdoor homomorphic commitments as a further cryptographic building block, making their deployment in practice not as easy as standard lattice-based Fiat-Shamir signatures. In this work, we present a new construction of $n$-out-of-$n$ distributed signatures. It is designed specifically for applications with small number of signers. Our construction follows the Fiat-Shamir with aborts paradigm, but solves the problem of large number of restarts without increasing the parameters by a factor of $n$ and utilizing any further cryptographic primitive. To demonstrate the practicality of our protocol, we provide a software implementation and concrete parameters aiming at 128 bits of security. Furthermore, we select concrete parameters for the construction by Damgård et al. and for the most recent lattice-based multi-signature scheme by Chen (CRYPTO 2023), and show that our approach provides a significant improvement in terms of all efficiency metrics. Our results also show that the multi-signature schemes by Damgård et al. and Chen as well as a multi-signature variant of our protocol produce signatures that are not smaller than a naive multi-signature derived from the concatenation of multiple standard signatures.

In this study, we investigate the newly developed low energy lightweight block cipher (LELBC), specifically designed for resource-constrained Internet of Things (IoT) devices in smart agriculture. The designers conducted a preliminary differential cryptanalysis of LELBC through mixed-integer linear programming (MILP). This paper further delves into LELBC’s differential characteristics in both single and related-key frameworks using MILP, identifying a nine-round differential characteristic with a probability of $2^{-60}$ in a single-key framework and a 12-round differential characteristic with a probability of $2^{-60}$ in a related-key framework.