6 papers
Improving ML Attacks on LWE with Data Repetition and Stepwise Regression
Alberto Alfarano, Eshika Saxena, Emily Wenger +2
The Learning with Errors (LWE) problem is a hard math problem in lattice-based cryptography. In the simplest case of binary secrets, it is the subset sum problem, with error. Effec…
TAPAS: Datasets for Learning the Learning with Errors Problem
Eshika Saxena, Alberto Alfarano, François Charton +2
AI-powered attacks on Learning with Errors (LWE), an important hard math problem in post-quantum cryptography, rival or outperform "classical" attacks on LWE under certain paramete…
HATSolver: Learning Groebner Bases with Hierarchical Attention Transformers
Mohamed Malhou, Ludovic Perret, Kristin Lauter
At NeurIPS 2024, Kera et al. introduced the use of transformers for computing Groebner bases, a central object in computer algebra with numerous practical applications. In this pap…
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…