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A Stochastic Model for Differential Side Channel Cryptanalysis

  • Werner Schindler
  • Kerstin Lemke
  • Christof Paar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3659)

Abstract

This contribution presents a new approach to optimize the efficiency of differential side channel cryptanalysis against block ciphers by advanced stochastic methods. We approximate the real leakage function within a suitable vector subspace. Under appropriate conditions profiling requires only one test key. For the key extraction we present a ‘minimum principle’ that solely uses deterministic data dependencies and the ‘maximum likelihood principle’ that additionally incorporates the characterization of the noise revealed during profiling. The theoretical predictions are accompanied and confirmed by experiments. We demonstrate that the adaptation of probability densities is clearly advantageous regarding the correlation method, especially, if multiple leakage signals at different times can be jointly evaluated. Though our efficiency at key extraction is limited by template attacks profiling is much more efficient which is highly relevant if the designer of a cryptosystem is bounded by the number of measurements in the profiling step.

Keywords

Differential Side Channel Cryptanalysis Stochastic Model Minimum Principle Maximum Likelihood Principle Power Analysis DPA Electromagnetic Analysis DEMA Template Attack 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Werner Schindler
    • 1
  • Kerstin Lemke
    • 2
  • Christof Paar
    • 2
  1. 1.Bundesamt für Sicherheit in der Informationstechnik (BSI)BonnGermany
  2. 2.Horst Görtz Institute for IT SecurityBochumGermany

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