Paper 2017/581
Time-Memory Trade-offs for Parallel Collision Search Algorithms
Monika Trimoska, Sorina Ionica, and Gilles Dequen
Abstract
Parallel versions of collision search algorithms require a significant amount of memory to store a proportion of the points computed by the pseudo-random walks. Implementations available in the literature use a hash table to store these points and allow fast memory access. We provide theoretical evidence that memory is an important factor in determining the runtime of this method. We propose to replace the traditional hash table by a simple structure, inspired by radix trees, which saves space and provides fast look-up and insertion. In the case of many-collision search algorithms, our variant has a constant-factor improved runtime. We give benchmarks that show the linear parallel performance of the attack on elliptic curves discrete logarithms and improved running times for meet-in-the-middle applications.
Note: The paper now has more implementation details and results.
Metadata
- Available format(s)
-
PDF
- Publication info
- Preprint. MINOR revision.
- Keywords
- discrete logarithmparallelismcollisionelliptic curvesmeet- in-the-middleattacktrade offradix tree
- Contact author(s)
- monika trimoska @ u-picardie fr
- History
- 2020-12-18: last of 3 revisions
- 2017-06-20: received
- See all versions
- Short URL
- https://ia.cr/2017/581
- License
-
CC BY
BibTeX
@misc{cryptoeprint:2017/581,
author = {Monika Trimoska and Sorina Ionica and Gilles Dequen},
title = {Time-Memory Trade-offs for Parallel Collision Search Algorithms},
howpublished = {Cryptology {ePrint} Archive, Paper 2017/581},
year = {2017},
url = {https://eprint.iacr.org/2017/581}
}
