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On the Optimality of Differential Fault Analyses on CLEFIA

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Mathematical Aspects of Computer and Information Sciences (MACIS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9582))

Abstract

In 2012, several Differential Fault Analyses on the AES cipher were analyzed from an information-theoretic perspective. This analysis exposed whether or not the leaked information was fully exploited. We apply the same approach to all existing Differential Fault Analyses on the CLEFIA cipher. We show that only some of these attacks are already optimal. We improve those analyses which did not exploit all information. With one exception, all attacks against CLEFIA-128 reach the theoretical limit after our improvement. Our improvement of an attack against CLEFIA-192 and CLEFIA-256 reduces the number of fault injections to the lowest possible number reached so far.

This work has been co-funded by the DFG as part of projects P1 and E3 within the CRC 1119 CROSSING and by the European Union’s Seventh Framework Program (FP7/2007-2013) under grant agreement n. 609611 (PRACTICE). The authors would like to thank TU Berlin, especially the Chair for Security in Telecommunications and Jean-Pierre Seifert, for valuable support.

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Notes

  1. 1.

    All figures in this section are taken from [13].

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Authors and Affiliations

  1. TU Darmstadt, Darmstadt, Germany

    Ágnes Kiss & Juliane Krämer

  2. TU Berlin, Berlin, Germany

    Juliane Krämer & Anke Stüber

Authors
  1. Ágnes Kiss
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  2. Juliane Krämer
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  3. Anke Stüber
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Correspondence to Ágnes Kiss .

Editor information

Editors and Affiliations

  1. Wilfrid Laurier University, Waterloo, Ontario, Canada

    Ilias S. Kotsireas

  2. Hamburg University of Technology, Hamburg, Germany

    Siegfried M. Rump

  3. New York University, New York, New York, USA

    Chee K. Yap

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Kiss, Á., Krämer, J., Stüber, A. (2016). On the Optimality of Differential Fault Analyses on CLEFIA. In: Kotsireas, I., Rump, S., Yap, C. (eds) Mathematical Aspects of Computer and Information Sciences. MACIS 2015. Lecture Notes in Computer Science(), vol 9582. Springer, Cham. https://doi.org/10.1007/978-3-319-32859-1_15

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  • DOI: https://doi.org/10.1007/978-3-319-32859-1_15

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-32859-1

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