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Scalable Key Rank Estimation (and Key Enumeration) Algorithm for Large Keys

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Smart Card Research and Advanced Applications (CARDIS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11389))

Abstract

Evaluation of security margins after a side-channel attack is an important step of side-channel resistance evaluation. The security margin indicates the brute force effort needed to recover the key given the leakages. In the recent years, several solutions for key rank estimation algorithms have been proposed. All these solutions give an interesting trade-off between the tightness of the result and the time complexity for symmetric key. Unfortunately, none of them has a linear complexity in the number of subkeys, hence these solutions are slow for large (asymmetric) keys. In this paper, we present a solution to obtain a key rank estimation algorithm with a reasonable trade-off between the efficiency and the tightness that is suitable for large keys. Moreover, by applying backtracking we obtain a parallel key enumeration algorithm.

V. Grosso—Part of this work was done while the author was at Radboud University Nijmegen, Digital Security Group, The Netherlands.

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Notes

  1. 1.

    https://eprint.iacr.org/2018/175.

  2. 2.

    https://eprint.iacr.org/2018/175.

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Acknowledgments

I thank the anonymous reviewers and Mathieu Carbone, Romain Poussier and François-Xavier Standaert for the improvements pointed out.

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Authors and Affiliations

  1. Univ Lyon, UJM-Saint-Etienne, CNRS, Laboratoire Hubert Curien UMR 5516, Saint-Etienne, France

    Vincent Grosso

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  1. Vincent Grosso
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Correspondence to Vincent Grosso .

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Editors and Affiliations

  1. Rambus - Cryptography Research, Rotterdam, Zuid-Holland, The Netherlands

    Begül Bilgin

  2. Nagravision, Cheseaux-sur-Lausanne, Vaud, Switzerland

    Jean-Bernard Fischer

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Grosso, V. (2019). Scalable Key Rank Estimation (and Key Enumeration) Algorithm for Large Keys. In: Bilgin, B., Fischer, JB. (eds) Smart Card Research and Advanced Applications. CARDIS 2018. Lecture Notes in Computer Science(), vol 11389. Springer, Cham. https://doi.org/10.1007/978-3-030-15462-2_6

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  • DOI: https://doi.org/10.1007/978-3-030-15462-2_6

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  • Online ISBN: 978-3-030-15462-2

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