Using the Capabilities of Artificial Neural Networks in the Cryptanalysis of Symmetric Lightweight Block Ciphers
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-51521-7_16
Reference21 articles.
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2. Liu, Y., Liang, H., Wang, W., & Wang, M. (2017). New Linear Cryptanalysis of Chinese Commercial Block Cipher Standard SM4. Security and Communication Networks, 2017, Article ID 1461520. https://doi.org/10.1155/2017/1461520
3. Abdurakhimov, B., Boykuziev, I., Allanov, O., & Xidirov, B. (2021). Differential characteristics of reflections of Kuznyechik encryption algorithm. In 2021 International Conference on Information Science and Communications Technologies (ICISCT) (pp. 1–4). Tashkent, Uzbekistan. https://doi.org/10.1109/ICISCT52966.2021.9670212
4. Fan, T., Li, L., Wei, Y., & Pasalic, E. (2022). Differential cryptanalysis of full-round ANU-II ultra-lightweight block cipher. International Journal of Distributed Sensor Networks, 18(9). https://doi.org/10.1177/15501329221119398
5. Blondeau, C., Leander, G., Nyberg, K.: Differential-Linear Cryptanalysis Revisited. J. Cryptol. 30(4), 859–888 (2017). https://doi.org/10.1007/s00145-016-9237-5
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