Abstract Fully Homomorphic Encryption (FHE) is a cryptographic primitive that allows
performing arbitrary operations on encrypted data. Since the conception of the idea in …

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 …

Given the recent progress in machine learning (ML), the cryptography community has
started exploring the applicability of ML methods to the design of new cryptanalytic …

Motivated by cryptographic applications, we investigate two machine learning approaches to
modular multiplication: namely circular regression and a sequence-to-sequence transformer …

The human ability to learn and reuse skills in a systematic manner is critical to our daily
routines. For example, having the skills for executing the basic arithmetic operations …

In their 2022 study, Kuang et al. introduced the multivariable polynomial public key (MPPK)
cryptography, which is a quantum-safe public key cryptosystem that leverages the inversion …

With the advent of quantum computers, traditional public key cryptosystems will no longer be
safe to use for the exchange of private information over the web. This shift necessitates the …

This volume contains the papers accepted for presentation at AFRICACRYPT 2024, the 15th
International Conference on the Theory and Application of Cryptographic Techniques in …

Sparse binary LWE secrets are under consideration for standardization for Homomorphic
Encryption and its applications to private computation. Known attacks on sparse binary LWE …

Almost pairwise independence (API) is a quantitative property of a class of functions that is
desirable in many cryptographic applications. This property is satisfied by Learning with …