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Title:
SALSA: Attacking Lattice Cryptography with Transformers
Authors: Emily Wenger, Mingjie Chen, Francois Charton, and Kristin Lauter
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.
ePrint: https://eprint.iacr.org/2022/935
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