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An Experimental Study of the BDD Approach for the Search LWE Problem

机译:搜索LWE问题的BDD方法的实验研究。

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The proved hardness of the Learning With Errors (LWE) problem, assuming the worst case intractability of classic lattice problems, has made it a standard building block in the recent design of lattice based cryptosystems. Nonetheless, a thorough understanding of the security of these schemes from the perspective of existing attacks remains an open problem In this manuscript, we report our implementation of the Bounded Distance Decoding (BDD) approach for solving the search LWE problem. We implement a parallel version of the pruned enumeration method of the BDD strategy proposed by Liu and Nguyen. In our implementation we use the embarrassingly parallel design so that the power of multi-cores can be fully utilized. We let each thread take a randomized basis and perform independent enumerations to find the solution instead of parallelizing the enumeration algorithm itself. Other optimizations include fine-tuning the BKZ block size, the enumeration bound and the pruning coefficients and the optimal dimension of the LWE problem. Experiments are done using the TU Darmstadt LWE challenge. Finally we compare our implementation with a recent parallel BDD implementation by Kirshanova et al. [18] and show that our implementation is more efficient.
机译:假设经典晶格问题的最坏情况难以解决,那么带错误学习(LWE)问题的经证明的硬度使其成为最近基于晶格的密码系统设计的标准构件。但是,从现有攻击的角度全面了解这些方案的安全性仍然是一个未解决的问题。在本手稿中,我们报告了为解决搜索LWE问题而实施的有界距离解码(BDD)方法的实现。我们实现了Liu和Nguyen提出的BDD策略的修剪枚举方法的并行版本。在我们的实现中,我们使用了令人尴尬的并行设计,以便可以充分利用多核的功能。我们让每个线程都随机化,并执行独立的枚举来找到解决方案,而不是并行化枚举算法本身。其他优化包括微调BKZ块大小,枚举范围和修剪系数以及LWE问题的最佳尺寸。实验是使用TU Darmstadt LWE挑战赛完成的。最后,我们将我们的实现与Kirshanova等人最近并行的BDD实现进行了比较。 [18],并表明我们的实施效率更高。

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