Cryptology ePrint Archive: Report 2014/489
A Genetic Algorithm for Searching Shortest Lattice Vector of SVP Challenge
Dan Ding and Guizhen Zhu and Xiaoyun Wang
Abstract: In this paper, we propose a genetic algorithm for solving the shortest vector problem (SVP) based on sparse integer representations of short vectors in lattices as chromesomes, which, we prove, can guarantee finding the shortest lattice vector under a Markov chain analysis. Moreover, we also suggest some improvements by introducing heuristic techniques: local search and heuristic pruning. The experimental results show that the genetic algorithm outperforms most enumeration algorithms in running time, and achieves the shortest vectors in larger dimensions under SVP challenge benchmarks.
Category / Keywords: Shortest Vector Problem (SVP), Lattice-Based Cryptography, Genetic Algorithm, Chromesome, and Local Search.
Date: received 19 Jun 2014, last revised 24 Jun 2014
Contact author: dingd09 at mails tsinghua edu cn
Available format(s): PDF | BibTeX Citation
Note: submitted to JCST
Version: 20140624:111347 (All versions of this report)
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