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Deep Learning-Based Cryptanalysis of Lightweight Block Ciphers
2020
Security and Communication Networks
Most of the traditional cryptanalytic technologies often require a great amount of time, known plaintexts, and memory. This paper proposes a generic cryptanalysis model based on deep learning (DL), where the model tries to find the key of block ciphers from known plaintext-ciphertext pairs. We show the feasibility of the DL-based cryptanalysis by attacking on lightweight block ciphers such as simplified DES, Simon, and Speck. The results show that the DL-based cryptanalysis can successfully
doi:10.1155/2020/3701067
fatcat:it4x43qyvrcebgeedsteaw2doq