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Improved the Automated Evaluation Algorithm Against Differential Attacks and Its Application to WARP

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Selected Areas in Cryptography (SAC 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13742))

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Abstract

This paper presents a heuristic approach to searching the key recovery-friendly distinguishers for block ciphers, which aims to attack more rounds with lower complexities. Firstly, we construct an SAT model to search for a set of distinguishers with the minimum number of active input-output words (and optimal probability). Subsequently, based on the discovered distinguishers, we select the advantageous distinguisher with fewer key bits involved in the key recovery phase. Finally, the guess-and-check for the key recovery attack is performed using the manual approach to compute the attack parameters accurately. By applying our new technique to \(\texttt{WARP}\) proposed in SAC 2020, we identify some 19-round and 20-round advantageous differentials. Simultaneously, the high-probability chain of Sbox leads to a stronger clustering effect of the differential trails for \(\texttt{WARP}\), so we effectively improve the probability of the advantageous distinguisher. Also, the first 25-round differential attacks are performed by extending a 19-round distinguisher and a 20-round distinguisher, respectively. The results cover 2 more rounds than the previous known differential attacks.

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Notes

  1. 1.

    https://github.com/msoos/cryptominisat.

  2. 2.

    https://web.archive.org/web/20131022021257/http:/www.sontrak.com/.

  3. 3.

    https://github.com/stp/stp.

  4. 4.

    http://www.gurobi.com.

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Acknowledgements

The authors would like to thank the reviewers for their valuable comments. This work is supported by the National Natural Science Foundation of China (No. 61702537, No. 62172427).

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Authors and Affiliations

  1. College of Science, National University of Defense Technology, Changsha, China

    Jiali Shi, Guoqiang Liu & Chao Li

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  1. Jiali Shi
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  2. Guoqiang Liu
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  3. Chao Li
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Correspondence to Guoqiang Liu .

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Editors and Affiliations

  1. Inria and École Polytechnique, Institut Polytechnique de Paris, Palaiseau, France

    Benjamin Smith

  2. Electrical and Computer Engineering, University of Windsor, Windsor, ON, Canada

    Huapeng Wu

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Shi, J., Liu, G., Li, C. (2024). Improved the Automated Evaluation Algorithm Against Differential Attacks and Its Application to WARP. In: Smith, B., Wu, H. (eds) Selected Areas in Cryptography. SAC 2022. Lecture Notes in Computer Science, vol 13742. Springer, Cham. https://doi.org/10.1007/978-3-031-58411-4_17

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  • DOI: https://doi.org/10.1007/978-3-031-58411-4_17

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