2 citations · 2 across the 5 of their papers we have counts for
4 papers · 1 filter
Making Hard Problems Easier with Custom Data Distributions and Loss Regularization: A Case Study in Modular Arithmetic
Eshika Saxena, Alberto Alfarano, François Charton +3
Recent work showed that ML-based attacks on Learning with Errors (LWE), a hard problem used in post-quantum cryptography, outperform classical algebraic attacks in certain settings…
Benchmarking Attacks on Learning with Errors
Emily Wenger, Eshika Saxena, Mohamed Malhou +2
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 HomomorphicEnc…
The cool and the cruel: separating hard parts of LWE secrets
Niklas Nolte, Mohamed Malhou, Emily Wenger +4
Sparse binary LWE secrets are under consideration for standardization for Homomorphic Encryption and its applications to private computation. Known attacks on sparse binary LWE sec…
Salsa Fresca: Angular Embeddings and Pre-Training for ML Attacks on Learning With Errors
Samuel Stevens, Emily Wenger, Cathy Li +4
Learning with Errors (LWE) is a hard math problem underlying recently standardized post-quantum cryptography (PQC) systems for key exchange and digital signatures. Prior work propo…