Feb. 5, 2024, 8:10 p.m. | Samuel Stevens Emily Wenger Cathy Li Niklas Nolte Eshika Saxena Fran\c{c}ois Charton Kristin Lauter

cs.CR updates on arXiv.org arxiv.org

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 proposed new machine learning (ML)-based attacks on LWE problems with small, sparse secrets, but these attacks require millions of LWE samples to train on and take days to recover secrets. We propose three key methods -- better preprocessing, angular embeddings and model pre-training -- to improve these attacks, speeding up preprocessing by $25\times$ and improving model …

angular attacks cryptography cs.cr cs.lg digital digital signatures errors exchange hard key machine machine learning math post-quantum post-quantum cryptography pqc problem problems quantum quantum cryptography secrets signatures systems train training work

Information Technology Specialist I, LACERA: Information Security Engineer

@ Los Angeles County Employees Retirement Association (LACERA) | Pasadena, CA

Senior Director, Artificial Intelligence & Machine Learning and Data Management

@ General Dynamics Information Technology | USA VA Falls Church - 3150 Fairview Park Dr (VAS095)

Test Engineer - Remote

@ General Dynamics Information Technology | USA VA Home Office (VAHOME)

Senior Principal Oracle Database Administrator

@ Everfox | Home Office - USA - Maryland

Director, Early Career and University Relations

@ Proofpoint | Texas

Enterprise Account Manager

@ Proofpoint | Geneva, Switzerland - Remote