Modern solvers for automated cryptanalysis

Abstract

Cryptanalysis plays a pivotal role in assessing and enhancing the security of cryptographic primitives, which underpin modern digital security in areas such as banking, telecommunications, and critical infrastructure. However, traditional cryptanalysis methods are often manually intensive and time-consuming. To address this, researchers have sought to automate the cryptanalysis process using mathematical modelling and advanced solvers, including SAT, Mixed-Integer Linear Programming (MILP), and Constraint Programming (CP).

This project explores the applicability of these solvers in modelling modern cryptanalysis techniques for real-world cryptographic primitives. By formulating cryptographic properties into a system of constraints solvable by optimisation tools, this paper aims to advance the efficiency and effectiveness of automated cryptanalysis.