An Improved BKW Algorithm For LWE With Binary Uniform Errors

Xi Qian, Jiu-fen Liu, Chunxiang Gu, Yonghui Zheng
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Abstract

The Learning with Errors (LWE) Problem has received much attention since its introduction and been widely used in cryptography. However the error sampled from Gaussian distribution affects efficiency of application based on LWE, the LWE variants with errors taken from uniform distribution came into being in 2013, which has an asymptotic complexity analysis.An improved BKW algorithm has been proposed to the LWE problem with binary uniform errors, and a study of the complexity of the algorithm is given in the paper. As a result, new bounds are provided for the concrete hardness of cryptography based on the variant, and parameter choices for quiet a few important algorithm.
具有二值均匀误差的LWE的改进BKW算法
带错误学习(LWE)问题自提出以来就受到了广泛的关注,并在密码学中得到了广泛的应用。然而,基于高斯分布的误差采样影响了基于LWE的应用效率,2013年出现了误差取自均匀分布的LWE变体,其具有渐近复杂性分析。针对具有二元均匀误差的LWE问题,提出了一种改进的BKW算法,并对该算法的复杂度进行了研究。在此基础上,给出了基于变量的具体密码学硬度的新界限,并给出了几个重要算法的参数选择。
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