Paper 2022/935 Original: eprint.iacr.org/2022/935 ↗
SALSA: Attacking Lattice Cryptography with Transformers
Abstract
Currently deployed public-key cryptosystems will be vulnerable to attacks by full- scale quantum computers. Consequently, quantum resistant cryptosystems are in high demand, and lattice-based cryptosystems, based on a hard problem known as Learning With Errors (LWE), have emerged as strong contenders for standardization. In this work, we train transformers to perform modular arithmetic and combine half-trained models with statistical cryptanalysis techniques to propose SALSA: a machine learning attack on LWE-based cryptographic schemes. SALSA can fully recover secrets for small-to-mid size LWE instances with sparse binary secrets, and may scale to attack real-world LWE-based cryptosystems.
Metadata
- Available format(s)
PDF- Category
- Attacks and cryptanalysis
- Publication info
- Preprint.
- History
- 2023-04-21: last updated
- 2022-07-18: published
- Short URL
- https://ia.cr/2022/935
- License
- https://creativecommons.org/licenses/by-sa/4.0/
BibTeX
@misc{cryptoeprint:2022/935,
author = {Emily Wenger and Mingjie Chen and Francois Charton and Kristin Lauter},
title = {SALSA: Attacking Lattice Cryptography with Transformers},
howpublished = {Cryptology {ePrint} Archive, Paper 2022/935},
year = {2022},
url = {https://eprint.iacr.org/2022/935}
}