SearcharxivSearch

arXiv subjects

Ryann Cartor

Publications and source records attributed to Ryann Cartor.

4 recordsLinked to original sources

Security Analysis of Integer Learning with Errors with Rejection Sampling

At ASIACRYPT 2018, a digital attack based on linear least squares was introduced for a variant of the learning with errors (LWE) problem which omits modular reduction known as the integer learning with errors problem (ILWE). In this paper, we present a theoretical and experimental study of the effectiveness of the attack when applied directly to small parameter ILWE instances found in popular digital signature schemes such as CRYSTALS-Dilithium which utilize rejection sampling. Unlike other studies which form ILWE instances based on additional information obtained from side-channel attacks, we take a more direct approach to the problem by constructing our ILWE instance from only the obtained signatures. We outline and introduce novel techniques in our simulation designs such as modular polynomial arithmetic via matrices in $\mathbb{R}$, as well as algorithms for handling large sample sizes efficiently. Our experimental results reinforce the proclaimed security of signature schemes based on ILWE. We additionally discuss the implications of our work and digital signatures as a whole in regards to real-world applications such as in Intelligent Transportation Systems (ITS).

cs.CR

Experimental Evaluation of Post-Quantum Homomorphic Encryption for Privacy-Preserving I2I Communication in ITS

This study experimentally evaluates the feasibility of post-quantum secure Homomorphic Encryption (HE) for privacy-preserving Infrastructure-to-Infrastructure (I2I) communication in Intelligent Transportation Systems (ITS). Unlike prior simulation-based efforts, this work implements three lattice-based HE schemes: Brakerski-Fan-Vercauteren (BFV), Brakerski-Gentry-Vaikuntanathan (BGV), and Cheon-Kim-Kim-Song (CKKS), within a real experimental pipeline representing roadside unit (RSU)-Cloud data exchange over Wi-Fi and Ethernet networks. The experiments benchmark encrypted addition and addition-plus-multiplication operations representing key analytical tasks, such as vehicle queue assessment and regional speed computation. Results show that while BFV achieves sub-5-second latency suitable for intersection-level analytics, BGV supports regional aggregation with 10 to 30-second updates. CKKS, though exhibiting higher latency (21-32 seconds), remains practical for minute-scale applications like eco-driving. These findings demonstrate that post-quantum HE can enable privacy-preserving ITS backhaul analytics when latency requirements align with application needs. The study also presents optimization pathways, including algorithmic tuning, network adaptation, and hardware acceleration, to reduce end-to-end delay.

cs.CR

Quadratic Modelings of Syndrome Decoding

This paper presents enhanced reductions of the bounded-weight and exact-weight Syndrome Decoding Problem (SDP) to a system of quadratic equations. Over $\mathbb{F}_2$, we improve on a previous work and study the degree of regularity of the modeling of the exact weight SDP. Additionally, we introduce a novel technique that transforms SDP instances over $\mathbb{F}_q$ into systems of polynomial equations and thoroughly investigate the dimension of their varieties. Experimental results are provided to evaluate the complexity of solving SDP instances using our models through Gr\"obner bases techniques.

cs.CR

Secure Distributed Matrix Multiplication with Precomputation

We consider the problem of secure distributed matrix multiplication in which a user wishes to compute the product of two matrices with the assistance of honest but curious servers. We show how to construct polynomial schemes for the outer product partitioning which take advantage of the user's ability to precompute, and provide bounds for our technique. We show that precomputation allows for a reduction in the order of the time complexity for the cases where the number of colluding servers is a fixed percentage of the number of servers. Furthermore, with precomputation, any percentage (less than 100%) of collusions can be tolerated, compared to the upper limit of 50% for the case without precomputation.

cs.IT