Parallel Improved Schnorr-Euchner Enumeration SE++ for the CVP and SVP
Paper in proceedings, 2016

The Closest Vector Problem (CVP) and the Shortest Vector Problem (SVP) are prime problems in lattice-based cryptanalysis, since they underpin the security of many lattice-based cryptosystems. Despite the importance of these problems, there are only a few CVP-solvers publicly available, and their scalability was never studied. This paper presents a scalable implementation of an enumeration-based CVP-solver for multi-cores, which can be easily adapted to solve the SVP. In particular, it achieves super-linear speedups in some instances on up to 8 cores and almost linear speedups on 16 cores when solving the CVP on a 50-dimensional lattice. Our results show that enumeration-based CVP-solvers can be parallelized as effectively as enumeration-based solvers for the SVP, based on a comparison with a state of the art SVP-solver. In addition, we show that we can optimize the SVP variant of our solver in such a way that it becomes 35%-60% faster than the fastest enumeration-based SVP-solver to date.

Author

Fabio Correia

Technische Universität Darmstadt

Artur Mariano

University of Minho

Alberto Proenca

University of Minho

Christian Bischof

Technische Universität Darmstadt

Erik Agrell

Chalmers, Signals and Systems, Kommunikationssystem, informationsteori och antenner, Communication Systems

24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2016, Heraklion, Crete, Greece, 17-19 February 2016

596-603 7445396

Subject Categories

Signal Processing

DOI

10.1109/PDP.2016.95

ISBN

978-1-4673-8775-0

More information

Latest update

3/29/2018