Abstract
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.
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Acknowledgements
The authors would like to show their sincere gratitude to the Scientific Analysis group (SAG), Defense Research and Development Organization (DRDO) for their invaluable support and collaboration throughout the course of this research. The authors would also like to thank Delhi Technological University (DTU), India for providing the opportunity to work in the field.
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Sajwan, A., Mishra, G. (2024). Comparative Analysis of ResNet and DenseNet for Differential Cryptanalysis of SPECK 32/64 Lightweight Block Cipher. In: Chaturvedi, A., Hasan, S.U., Roy, B.K., Tsaban, B. (eds) Cryptology and Network Security with Machine Learning. ICCNSML 2023. Lecture Notes in Networks and Systems, vol 918. Springer, Singapore. https://doi.org/10.1007/978-981-97-0641-9_34
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DOI: https://doi.org/10.1007/978-981-97-0641-9_34
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