A Random Sampling Algorithm for SVP Challenge Based on y-Sparse Representations of Short Lattice Vectors
Dan Ding, Guizhen Zhu · 2014
In this paper, we propose a novel random sampling algorithm for the shortest vector problem (SVP) based on the y-sparse representations of the short lattice vectors. The experimental results show that the random sampling algorithm outperforms the other two SVP algorithms under the benchmarks of SVP challenge[1]. Therefore, the random sampling algorithm is an efficient SVP solver for the shortest vector problem.