Volume 14, Number 5

Encryption Modes Identification of Block Ciphers based on Machine Learning


Ruiqi Xia1, Manman Li2 and Shaozhen Chen2, 1Information Engineering University, China, 2State Key Laboratory of Mathematical Engineering and Advanced Computing, Kexue Avenue, China


Encryption modes affect the security of block ciphers. This paper proposes a new approach for identifying encryption modes based on machine learning and feature engineering. In the conditions of random keys and initialization vectors, five encryption modes are used for identification. Each mode is encrypted by several block ciphers. By comparing with previous work, we have overcome the shortcomings and improved the accuracy of identification by about 30% to 40%. The experiments improve the existing results and can effectively help cryptanalysts recover the keys.


Machine learning, Cryptography, Block ciphers, Feature engineering, Encryption modes, Ciphers identification.