32 citations · 34 across the 8 of their papers we have counts for
9 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…
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…
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…
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…
Machine learning for modular multiplication
Kristin Lauter, Cathy Yuanchen Li, Krystal Maughan +2
Motivated by cryptographic applications, we investigate two machine learning approaches to modular multiplication: namely circular regression and a sequence-to-sequence transformer…
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…
Shorter quantum circuits via single-qubit gate approximation
Vadym Kliuchnikov, Kristin Lauter, Romy Minko +2
We give a novel procedure for approximating general single-qubit unitaries from a finite universal gate set by reducing the problem to a novel magnitude approximation problem, achi…