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Improved Differential-neural Cryptanalysis for Round-reduced Simeck32/64
Inspired by this framework, we develop the Inception neural network that is compatible with the round function of Simeck to improve the accuracy of the neural distinguishers, thus improving the accuracy of (9-12)-round neural distinguishers for Simeck32/64.
Improved (Related-key) Differential-based Neural Distinguishers for SIMON and SIMECK Block Ciphers
In CRYPTO 2019, Gohr made a pioneering attempt and successfully applied deep learning to the differential cryptanalysis against NSA block cipher SPECK32/64, achieving higher accuracy than the pure differential distinguishers.
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