Recent Advances in Machine Learning for Differential Cryptanalysis
摘要
Differential cryptanalysis has proven to be a powerful tool to identify weaknesses in symmetric-key cryptographic systems such as block ciphers. Recent advances have shown that machine learning methods are able to produce very strong distinguishers for certain cryptographic systems. This has generated a large interest in the topic of machine learning for differential cryptanalysis as evidenced by a growing body of work in the last few years. In this paper we aim to provide a guide to the current state of the art in this topic in the hope that a unified view can better highlight the challenges and opportunities for researchers joining the field.