论文标题

RQC对基于等级的密码学进行了重新审视和更多的密码分析

RQC revisited and more cryptanalysis for Rank-based Cryptography

论文作者

Bidoux, Loïc, Briaud, Pierre, Bros, Maxime, Gaborit, Philippe

论文摘要

我们提出了两个主要贡献:首先,我们通过引入新的有效变化,尤其是新的代码,即增强的Gabidulin代码来重新审视加密方案列表准循环(RQC);其次,我们提出了针对等级支持学习(RSL),非殖民排名解码(NHRSD)和非均匀等级支持学习(NHRSL)问题的新攻击。 RSL对于所有最近基于等级的加密系统都是原始的,例如Durandal(Aragon等,Eurocrypt 2019)或具有多种综合症(ARXIV:2206.11961)的LRPC,此外,NHRSD和NHRSL与RSL一起,与RSL一起使用RSL,是我们新的新阶段的核心。我们提出的新攻击都是两种类型的:组合和代数。对于所有这些攻击,我们对它们的复杂性进行了精确的分析。总体而言,当将所有这些新的RQC方案的新改进都放在一起时,他们的安全性通过我们的不同攻击进行了评估时,与以前的RQC版本相比,它们能够获得50%的参数尺寸。更确切地说,对于具有非结构化公共密钥矩阵的RQC方案,我们提供了非常具竞争力的参数,约为11个KBYTES。目前,这是唯一具有如此短的参数的方案,其安全性仅依赖于纯随机实例而没有任何掩盖假设,与McEliece样方案相反。最后,在考虑非均匀错误的情况时,我们的方案允许达到甚至较小的参数。

We propose two main contributions: first, we revisit the encryption scheme Rank Quasi-Cyclic (RQC) by introducing new efficient variations, in particular, a new class of codes, the Augmented Gabidulin codes; second, we propose new attacks against the Rank Support Learning (RSL), the Non-Homogeneous Rank Decoding (NHRSD), and the Non-Homogeneous Rank Support Learning (NHRSL) problems. RSL is primordial for all recent rank-based cryptosystems such as Durandal (Aragon et al., EUROCRYPT 2019) or LRPC with multiple syndromes (arXiv:2206.11961), moreover, NHRSD and NHRSL, together with RSL, are at the core of our new schemes. The new attacks we propose are of both types: combinatorial and algebraic. For all these attacks, we provide a precise analysis of their complexity. Overall, when all of these new improvements for the RQC scheme are put together, and their security evaluated with our different attacks, they enable one to gain 50% in parameter sizes compared to the previous RQC version. More precisely, we give very competitive parameters, around 11 KBytes, for RQC schemes with unstructured public key matrices. This is currently the only scheme with such short parameters whose security relies solely on pure random instances without any masking assumptions, contrary to McEliece-like schemes. At last, when considering the case of Non-Homogeneous errors, our scheme permits to reach even smaller parameters.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源