Author:
Sun Shuo,Zhou Yongbin,Ji Yunfeng,Zhang Rui,Tao Yang
Abstract
AbstractGaussian sampling over the integers is one of the fundamental building blocks of lattice-based cryptography. Among the extensively used trapdoor sampling algorithms, it is ineluctable until now. Under the influence of numerous side-channel attacks, it is still challenging to construct a Gaussian sampler that is generic, efficient, and resistant to timing attacks. In this paper, our contribution is three-fold. First, we propose a secure, efficient exponential Bernoulli sampling algorithm. It can be applied to Gaussian samplers based on rejection samplings. We apply it to FALCON, a candidate of round 3 of the NIST post-quantum cryptography standardization project, and reduce its signature generation time by 13–14%. Second, we develop an isochronous Gaussian sampler based on rejection sampling. Our Algorithm can securely sample from Gaussian distributions with different standard deviations and arbitrary centers. We apply it to PALISADE (S&P 2018), an open-source lattice-based cryptography library. During the online phase of trapdoor sampling, the running time of the G-lattice sampling algorithm is reduced by 44.12% while resisting timing attacks. Third, we improve the efficiency of the COSAC sampler (PQC 2020). The new COSAC sampler is 1.46x–1.63x faster than the original and has the lowest expected number of trials among all Gaussian samplers based on rejection samplings. But it needs a more efficient algorithm sampling from the normal distribution to improve its performance.
Funder
National Natural Science Foundation of China
Beijing Natural Science Foundation
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Networks and Communications,Information Systems,Software
Cited by
3 articles.
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