Comparative Analysis of ResNet and DenseNet for Differential Cryptanalysis of SPECK 32/64 Lightweight Block Cipher

This research paper explores the vulnerabilities of the lightweight block cipher SPECK 32/64 through the application of differential analysis and deep learning techniques. The primary objectives of the study are to investigate the cipher’s weaknesses and to compare the effectiveness of ResNet as used by Aron Gohr at Crypto2019 and DenseNet. The methodology involves conducting an analysis of differential characteristics to identify potential weaknesses in the cipher’s structure. Experimental results and analysis demonstrate the efficacy of both approaches in compromising the security of SPECK 32/64.