TAPAS: Datasets for Learning the Learning with Errors Problem

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 parameter settings. Despite the promise of this approach, a dearth of accessible data limits AI practitioners' ability to study and improve these attacks. Creating LWE data for AI model training is time-and compute-intensive and requires significant domain expertise.