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Conference Papers Year : 2021

Efficient Methods to Search for Best Differential Characteristics on SKINNY

Abstract

Evaluating resistance of ciphers against differential cryptanalysis is essential to define the number of rounds of new designs and to mount attacks derived from differential cryptanalysis. In this paper, we propose automatic tools to find the best differential characteristics on the SKINNY block cipher. As usually done in the literature, we split this search in two stages denoted by Step 1 and Step 2. In Step 1, we aim at finding all truncated differential characteristics with a low enough number of active Sboxes. Then, in Step 2, we try to instantiate each difference value while maximizing the overall differential characteristic probability. We solve Step 1 using an ad-hoc method inspired from the work of Fouque et al. whereas Step 2 is modelized for the Choco-solver library as it seems to outperform all previous methods on this stage. Notably, for SKINNY-128 in the SK model and for 13 rounds, we retrieve the results of Abdelkhalek et al. within a few seconds (to compare with 16 days) and we provide, for the first time, the best differential related-tweakey characteristics up to 14 rounds for the TK1 model. Regarding the TK2 and the TK3 models, we were not able to test all the solutions Step 1, and thus the differential characteristics we found up to 16 and 17 rounds are not necessarily optimal.
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Dates and versions

hal-03040548 , version 1 (04-12-2020)
hal-03040548 , version 2 (15-04-2021)

Identifiers

Cite

Stéphanie Delaune, Patrick Derbez, Paul Huynh, Marine Minier, Victor Mollimard, et al.. Efficient Methods to Search for Best Differential Characteristics on SKINNY. ACNS 2021 - 19th International Conference on Applied Cryptography and Network Security, Jun 2021, Kamakura, Japan. pp.184-207, ⟨10.1007/978-3-030-78375-4_8⟩. ⟨hal-03040548v2⟩
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