Benchmarking Attacks on Learning with Errors
Emily Wenger, Eshika Saxena, Mohamed Malhou, Ellie Thieu, Kristin, Lauter

TL;DR
This paper benchmarks various attacks on Learning with Errors (LWE) cryptography using standardized parameters, providing new insights into their practical security and extending attack methods with open-source code.
Contribution
It introduces the first concrete benchmarks for LWE secret recovery on standardized parameters, extending attack techniques and scaling up existing methods.
Findings
SALSA and Cool & Cruel recover secrets in 28-36 hours
MitM attack solves Decision-LWE for low Hamming weight in under an hour
uSVP attacks do not recover secrets after extensive runtime
Abstract
Lattice cryptography schemes based on the learning with errors (LWE) hardness assumption have been standardized by NIST for use as post-quantum cryptosystems, and by HomomorphicEncryption.org for encrypted compute on sensitive data. Thus, understanding their concrete security is critical. Most work on LWE security focuses on theoretical estimates of attack performance, which is important but may overlook attack nuances arising in real-world implementations. The sole existing concrete benchmarking effort, the Darmstadt Lattice Challenge, does not include benchmarks relevant to the standardized LWE parameter choices - such as small secret and small error distributions, and Ring-LWE (RLWE) and Module-LWE (MLWE) variants. To improve our understanding of concrete LWE security, we provide the first benchmarks for LWE secret recovery on standardized parameters, for small and low-weight…
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Taxonomy
TopicsAdversarial Robustness in Machine Learning · Machine Learning and Algorithms
