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Monte Carlo Tree Search for Automatic Differential Characteristics Search: Application to SPECK

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Progress in Cryptology – INDOCRYPT 2022 (INDOCRYPT 2022)

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Abstract

The search for differential characteristics on block ciphers is a difficult combinatorial problem. In this paper, we investigate the performances of an AI-originated technique, Single Player Monte-Carlo Tree Search (SP-MCTS), in finding good differential characteristics on ARX ciphers, with an application to the block cipher SPECK. In order to make this approach competitive, we include several heuristics, such as the combination of forward and backward searches, and achieve significantly faster results than state-of-the-art works that are not based on automatic solvers. We reach 9, 11, 13, 13 and 15 rounds for SPECK32, SPECK48, SPECK64, SPECK96 and SPECK128 respectively. In order to build our algorithm, we revisit Lipmaa and Moriai’s algorithm for listing all optimal differential transitions through modular addition, and propose a variant to enumerate all transitions with probability close (up to a fixed threshold) to the optimal, while fixing a minor bug in the original algorithm.

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Correspondence to Matteo Rossi .

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Appendices

Appendix a All Optimal Characteristics on SPECK32

See Table 2.

Table 2. A list of all the differential characteristics with weight 30 in SPECK32.

Appendix B Best Characteristics Found with Our Method

See Table 3.

Table 3. Differential characteristics related to the results listed in Table 1.

Appendix C Pseudocode for the Search Algorithm

figure c

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Bellini, E., Gerault, D., Protopapa, M., Rossi, M. (2022). Monte Carlo Tree Search for Automatic Differential Characteristics Search: Application to SPECK. In: Isobe, T., Sarkar, S. (eds) Progress in Cryptology – INDOCRYPT 2022. INDOCRYPT 2022. Lecture Notes in Computer Science, vol 13774. Springer, Cham. https://doi.org/10.1007/978-3-031-22912-1_17

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  • DOI: https://doi.org/10.1007/978-3-031-22912-1_17

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  • Online ISBN: 978-3-031-22912-1

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