Welcome to the resource topic for 2022/886
Title:
Deep Learning based Cryptanalysis of Lightweight Block Ciphers, Revisited
Authors: Hyunji Kim, Sejin Lim, Yeajun Kang, Wonwoong Kim, and Hwajeong Seo
Abstract:Cryptanalysis is to infer the secret key of cryptography algorithm. There are brute-force attack, differential attack, linear attack, and chosen plaintext attack. With the development of artificial intelligence, deep learning-based cryptanalysis has been actively studied. There are works in which known-plaintext attacks against lightweight block ciphers, such as S-DES, have been performed. In this paper, we propose a cryptanalysis method based on the-state-of-art deep learning technologies (e.g. residual connections and gated linear units) for lightweight block ciphers (e.g. S-DES and S-AES). The number of parameters required for training is significantly reduced by 93.16~% and the average of bit accuracy probability increased by about 5.3~%, compared with previous work.
ePrint: https://eprint.iacr.org/2022/886
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