International Association
for Cryptologic Research

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