International Association
for Cryptologic Research

With the growing adoption of cloud computing, the ability to store data and delegate computations to powerful and affordable cloud servers have become advantageous for both companies and individual users. However, the security of cloud computing has emerged as a significant concern. Particularly, Cloud Service Providers (CSPs) cannot assure data confidentiality and computations integrity in mission-critical applications. In this paper, we propose a confidential and verifiable delegation scheme that advances and overcomes major performance limitations of existing Secure Multiparty Computation (MPC) and Zero Knowledge Proof (ZKP). Secret-shared Data and delegated computations to multiple cloud servers remain completely confidential as long as there is at least one honest MPC server. Moreover, results are guaranteed to be valid even if all the participating servers are malicious. Specifically, we design an efficient protocol based on interactive proofs, such that most of the computations generating the proof can be done locally on each server. In addition, we propose a special protocol for matrix multiplication where the overhead of generating the proof is asymptotically smaller than the time to evaluate the result in MPC. Experimental evaluation demonstrates that our scheme significantly outperforms prior work, with the online prover time being 1-2 orders of magnitude faster. Notably, in the matrix multiplication protocol, only a minimal 2% of the total time is spent on the proof generation. Furthermore, we conducted tests on machine learning inference tasks. We executed the protocol for a fully-connected neural network with 3 layers on the MNIST dataset and it takes 2.6 seconds to compute the inference in MPC and generate the proof, 88× faster than prior work. We also tested the convolutional neural network of Lenet with 2 convolution layers and 3 dense layers and the running time is less than 300 seconds across three servers.

We study the possibility of schemes whose public parameters have been generated along with a backdoor. We consider the goal of the big-brother adversary to be two-fold: It desires utility (it can break the scheme) but also exclusivity (nobody else can). Starting with hash functions, we give new, strong definitions for these two goals, calling the combination high effectiveness. We then present a construction of a backdoored hash function that is highly effective, meaning provably meets our new definition. As an application, we investigate forgery of X.509 certificates that use this hash function. We then consider signatures, again giving a definition of high effectiveness, and showing that it can be achieved. But we also give some positive results, namely that for the Okamoto and Katz-Wang signature schemes, certain natural backdoor strategies are provably futile. Our backdoored constructions serve to warn that backdoors can be more powerful and damaging than previously conceived, and to help defenders and developers identify potential backdoors by illustrating how they might be built. Our positive results illustrate that some schemes do offer more backdoor resistance than others, which may make them preferable.

The Gradient Boosting Decision Tree (GBDT) is a well-known machine learning algorithm, which achieves high performance and outstanding interpretability in real-world scenes such as fraud detection, online marketing and risk management. Meanwhile, two data owners can jointly train a GBDT model without disclosing their private dataset by executing secure Multi-Party Computation (MPC) protocols. In this work, we propose NodeGuard, a highly efficient two party computation (2PC) framework for large-scale GBDT training and inference. NodeGuard guarantees that no sensitive intermediate results are leaked in the training and inference. The efficiency advantage of NodeGuard is achieved by applying a novel keyed bucket aggregation protocol, which optimizes the communication and computation complexity globally in the training. Additionally, we introduce a probabilistic approximate division protocol with an optimization for re-scaling, when the divisor is publicly known. Finally, we compare NodeGuard to state-of-the-art frameworks, and we show that NodeGuard is extremely efficient. It can improve the privacy preserving GBDT training performance by a factor of 5.0 to 131 in LAN and 2.7 to 457 in WAN.

Cryptographic protocols are hard to design and prove correct, as witnessed by the ever-growing list of attacks even on protocol standards. Symbolic models of cryptography enable automated formal security proofs of such protocols against an idealized cryptographic model, which abstracts away from the algebraic properties of cryptographic schemes and thus misses attacks. Computational models of cryptography yield rigorous guarantees but support at present only interactive proofs and/or restricted classes of protocols (e.g., stateless ones). A promising approach is given by the computationally complete symbolic attacker (CCSA) model, formalized in the BC Logic, which aims at bridging and getting the best of the two worlds, obtaining cryptographic guarantees by symbolic protocol analysis. The BC Logic is supported by a recently developed interactive theorem prover, namely Squirrel, which enables machine-checked interactive security proofs, as opposed to automated ones, thus requiring expert knowledge both in the cryptographic space as well as on the reasoning side.

In this paper, we introduce the CryptoVampire cryptographic protocol verifier, which for the first time fully automates proofs of trace properties in the BC Logic. The key technical contribution is a first-order formalization of protocol properties with tailored handling of subterm relations. As such, we overcome the burden of interactive proving in higher-order logic and automatically establish soundness of cryptographic protocols using only first-order reasoning. Our first-order encoding of cryptographic protocols is challenging for various reasons. On the theoretical side, we restrict full first-order logic with cryptographic axioms to ensure that, by losing the expressivity of the higher-order BC Logic, we do not lose soundness of cryptographic protocols in our first-order encoding. On the practical side, CryptoVampire integrates dedicated proof techniques using first-order saturation algorithms and heuristics, which all together enable leveraging the state-of-the-art Vampire first-order automated theorem prover as the underlying proving engine of CryptoVampire. Our experimental results showcase the effectiveness of CryptoVampire as a standalone verifier as well as in terms of automation support for Squirrel.

Cache side-channels are a major threat to cryptographic implementations, particularly block ciphers. Traditional manual hardening methods transform block ciphers into Boolean circuits, a practice refined since the late 90s. The only existing automatic approach based on Boolean circuits achieves security but suffers from performance issues. This paper examines the use of Lookup Tables (LUTs) for automatic hardening of block ciphers against cache side-channel attacks. We present a novel method combining LUT-based synthesis with quantitative static analysis in our HyCaMi framework. Applied to seven block cipher implementations, HyCaMi shows significant improvement in efficiency, being 9.5$\times$ more efficient than previous methods, while effectively protecting against cache side-channel attacks. Additionally, for the first time, we explore balancing speed with security by adjusting LUT sizes, providing faster performance with slightly reduced leakage guarantees, suitable for scenarios where absolute security and speed must be balanced.

We reflect on our experiences analysing cryptography deployed “in the wild” and give recommendations to fellow researchers about this process.

In 2021, Sterner proposed a commitment scheme based on supersingular isogenies. For this scheme to be binding, one relies on a trusted party to generate a starting supersingular elliptic curve of unknown endomorphism ring. In fact, the knowledge of the endomorphism ring allows one to compute an endomorphism of degree a power of a given small prime. Such an endomorphism can then be split into two to obtain two different messages with the same commitment. This is the reason why one needs a curve of unknown endomorphism ring, and the only known way to generate such supersingular curves is to rely on a trusted party or on some expensive multiparty computation. We observe that if the degree of the endomorphism in play is well chosen, then the knowledge of the endomorphism ring is not sufficient to efficiently compute such an endomorphism and in some particular cases, one can even prove that endomorphism of a certain degree do not exist. Leveraging these observations, we adapt Sterner's commitment scheme in such a way that the endomorphism ring of the starting curve can be known and public. This allows us to obtain isogeny-based commitment schemes which can be instantiated without trusted setup requirements.

In this article, we focus on deriving an easily implementable and efficient method of constructing units of the group ring of dihedral group. We provide a necessary and sufficient condition that relates the units in the group ring of dihedral group with the units in the group ring of cyclic group. Using this relation and the methods available for inversion in the group ring of the cyclic group, we introduce an algorithm to construct units efficiently and check its performance experimentally.

This paper introduces a new method for training decision trees and random forests using CKKS homomorphic encryption (HE) in cloud environments, enhancing data privacy from multiple sources. The innovative Homomorphic Binary Decision Tree (HBDT) method utilizes a modified Gini Impurity index (MGI) for node splitting in encrypted data scenarios. Notably, the proposed training approach operates in a single cloud security domain without the need for decryption, addressing key challenges in privacy-preserving machine learning. We also propose an efficient method for inference utilizing only addition for path evaluation even when both models and inputs are encrypted, achieving O(1) multiplicative depth. Experiments demonstrate that this method surpasses the previous study by Akavia et al.'s by at least 3.7 times in the speed of inference. The study also expands to privacy-preserving random forests, with GPU acceleration ensuring feasibly efficient performance in both training and inference.

Determining the complexity of computing Gröbner bases is an important problem both in theory and in practice, and for that the solving degree plays a key role. In this paper, we study the solving degrees of affine semi-regular sequences and their homogenized sequences. Some of our results are considered to give mathematically rigorous proofs of the correctness of methods for computing Gröbner bases of the ideal generated by an affine semi-regular sequence. This paper is a sequel of the authors’ previous work and gives additional results on the solving degrees and important behaviors of Gröbner basis computation.

Recent improvements to garbled circuits are mainly focused on reducing their size. The state-of-the-art construction of Rosulek and Roy (Crypto 2021) requires $1.5\kappa$ bits for garbling AND gates in the free-XOR setting. This is below the previously proven lower bound $2\kappa$ in the linear garbling model of Zahur, Rosulek, and Evans (Eurocrypt 2015).

Recently, Ashur, Hazay, and Satish (eprint 2024/389) proposed a scheme that requires $4/3\kappa + O(1)$ bits for garbling AND gates. Precisely they extended the idea of slicing introduced by Rosulek and Roy to garble 3-input gates of the form $g(u,v,w) := u(v+w)$. By setting $w = 0$, it can be used to garble AND gates with the improved communication costs.

However, in this paper, we observe that the scheme proposed by Ashur, Hazy, and Satish leaks information on the permute bits, thereby allowing the evaluator to reveal information on the private inputs. To be precise, we show that in their garbling scheme, the evaluator can compute the bits $\alpha$ and $\beta + \gamma$, where $\alpha$, $\beta$, and $\gamma$ are the private permute bits of the input labels $A$, $B$, and $C$, respectively.

Fischlin's transform (CRYPTO 2005) is an alternative to the Fiat-Shamir transform that enables straight-line extraction when proving knowledge. In this work we focus on the problem of using the Fischlin transform to construct UC-secure zero-knowledge from Sigma protocols, since UC security -- that guarantees security under general concurrent composition -- requires straight-line (non-rewinding) simulators. We provide a slightly simplified transform that is much easier to understand, and present algorithmic and implementation optimizations that significantly improve the running time. It appears that the main obstacles to the use of Fischlin in practice is its computational cost and implementation complexity (with multiple parameters that need to be chosen). We provide clear guidelines and a simple methodology for choosing parameters, and show that with our optimizations the running-time is far lower than expected. For just one example, on a 2023 MacBook, the cost of proving the knowledge of discrete log with Fischlin is only 0.41ms (on a single core). We also extend the transform so that it can be applied to batch proofs, and show how this can be much more efficient than individually proving each statement. As a contribution of independent interest, we present a new algorithm for polynomial evaluation on any series of sequential points that does not require roots of unity. We hope that this paper will both encourage and help practitioners implement the Fischlin transform where relevant.

Biometric authentication eliminates the need for users to remember secrets and serves as a convenient mechanism for user authentication. Traditional implementations of biometric-based authentication store sensitive user biometry on the server and the server becomes an attractive target of attack and a source of large-scale unintended disclosure of biometric data. To mitigate the problem, we can resort to privacy-preserving computation and store only protected biometrics on the server. While a variety of secure computation techniques is available, our analysis of privacy-preserving biometric computation and biometric authentication constructions revealed that available solutions fall short of addressing the challenges of privacy-preserving biometric authentication. Thus, in this work we put forward new constructions to address the challenges.

Our solutions employ a helper server and use strong threat models, where a client is always assumed to be malicious, while the helper server can be semi-honest or malicious. We also determined that standard secure multi-party computation security definitions are insufficient to properly demonstrate security in the two-phase (enrollment and authentication) entity authentication application. We thus extend the model and formally show security in the multi-phase setting, where information can flow from one phase to another and the set of participants can change between the phases. We implement our constructions and show that they exhibit practical performance for authentication in real time.

The sumcheck protocol is an interactive protocol for verifying the sum of a low-degree polynomial over a hypercube. This protocol is widely used in practice, where an efficient implementation of the (honest) prover algorithm is paramount. Prior work contributes highly-efficient prover algorithms for the notable special case of multilinear polynomials (and related settings): [CTY11] uses logarithmic space but runs in superlinear time; in contrast, [VSBW13] runs in linear time but uses linear space. In this short note, we present a family of prover algorithms for the multilinear sumcheck protocol that offer new time-space tradeoffs. In particular, we recover the aforementioned algorithms as special cases. Moreover, we provide an efficient implementation of the new algorithms, and our experiments show that the asymptotics translate into new concrete efficiency tradeoffs.

In "Keeping up with the KEMs" Cremers et al. introduced various binding models for KEMs. The authors show that ML-KEM is LEAK-BIND-K-CT and LEAK-BIND-K-PK, i.e. binding the ciphertext and the public key in the case of an adversary having access, but not being able to manipulate the key material. They further conjecture that ML-KEM also has MAL-BIND-K-PK, but not MAL-BIND-K-CT, the binding of public key or ciphertext to the shared secret in the case of an attacker with the ability to manipulate the key material. This short paper demonstrates that ML-KEM does neither have MALBIND-K-CT nor MAL-BIND-K-PK, due to the attacker being able to produce mal-formed private keys, giving concrete examples for both. We also suggest mitigations, and sketch a proof for binding both ciphertext and public key when the attacker is not able to manipulate the private key as liberally.

In their paper, Wei et al. proposed a lightweight protocol for conditional privacy-preserving authentication in VANET. The protocol aims to achieve ultra-low transmission delay and efficient system secret key (SSK) updating. Their protocol uses a signature scheme with message recovery to authenticate messages. This scheme provides security against adaptively chosen message attacks. However, our analysis reveals a critical vulnerability in the scheme. It is susceptible to replay attacks, meaning a malicious vehicle can replay a message multiple times at different timestamps. This action undermines the overall effectiveness of conditional privacy. We suggest possible solutions to address these vulnerabilities and enhance the security of VANET communication.

In this paper, we propose a novel isogeny-based public key encryption (PKE) scheme named LIT-SiGamal. This is based on a LIT diagram and SiGamal. SiGamal is an isogeny-based PKE scheme that uses a commutative diagram with an auxiliary point. LIT-SiGamal uses a LIT diagram which is a commutative diagram consisting of large-degree horizontal isogenies and relatively small-degree vertical isogenies, while the original SiGamal uses a CSIDH diagram.

A strength of LIT-SiGamal is efficient encryption and decryption. QFESTA is an isogeny-based PKE scheme proposed by Nakagawa and Onuki, which is a relatively efficient scheme in isogeny-based PKE schemes. In our experimentation with our proof-of-concept implementation, the computational time of the encryption of LIT-SiGamal is as efficient as that of QFESTA, and that of the decryption of LIT-SiGamal is about $5$x faster than that of QFESTA.

We describe a small tweak to Cuckoo filters that allows securing them under insertions using the techniques from Filić et al. (ACM CCS 2022), without the need for an outer PRF call.

Given that the tropical Stickel protocol and its variants are all vulnerable to the generalized Kotov-Ushakov attack, we suggest employing the max-min semiring and, more generally, max-$T$ semiring where the multiplication is based on a $T-$norm, as a framework to implement the Stickel protocol. While the Stickel protocol over max-min semiring or max-$T$ semiring remains susceptible to a form of Kotov-Ushakov attack, we demonstrate that it exhibits significantly increased resistance against this attack when compared to the tropical (max-plus) implementation.

Cryptographic agility, or crypto-agility, is a design feature that enables agile updates to new cryptographic algorithms and standards without the need to modify or replace the surrounding infrastructure. This paper examines the prerequisites for crypto-agility and proposes its desired design feature. More specifically, we investigate the design characteristics of widely deployed cybersecurity paradigms, i.e., zero trust, and apply its design feature to crypto-agility, achieving greater visibility and automation in cryptographic management.