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Profiling Power Analysis Attack Based on Multi-layer Perceptron Network

  • Chapter
Computational Problems in Science and Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 343))

Abstract

In 2013, an innovative method of power analysis was presented in Martinasek and Zeman (Radioengineering 22(2), IF 0.687, 2013) and Martinasek et al. (Smart Card Research and Advanced Applications. Lecture Notes in Computer Science. Springer International Publishing, New York, 2014). Realized experiments proved that the proposed method based on Multi-Layer Perceptron (MLP) can provide almost 100 % success rate. This description based on the first-order success rate is not appropriate enough. Moreover, the above mentioned works contain other lacks: the MLP has not been compared with other well-known attacks, an adversary uses too many points of power trace and a general description of the MLP method was not provided. In this paper, we eliminate these weaknesses by introducing the first fair comparison of power analysis attacks based on the MLP and templates. The comparison is accomplished by using the identical data sets, number of interesting points and guessing entropy as a metric. The first data set created contains the power traces of an unprotected AES implementation in order to classify the secret key stored. The second and third data sets were created independently from public available power traces corresponding to a masked AES implementation (DPA Contest v4). Secret offset is revealed depending on the number of interesting points and power traces in this experiment. Moreover, we create a general description of the MLP attack.

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Notes

  1. 1.

    The size of the covariance matrix grows quadratically with the number of points in the trace, more information in [9].

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Acknowledgements

Research described in this paper was financed by the National Sustainability Program under grant LO1401. For the research, infrastructure of the SIX Center was used.

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Authors and Affiliations

  1. Department of Telecommunications, Brno University of Technology, Technicka 12, 612 00, Brno, Czech Republic

    Zdenek Martinasek & Lukas Malina

  2. Department of Garden and Landscape Architecture, Mendel University in Brno, Valticka 337, 691 44, Lednice, Czech Republic

    Krisztina Trasy

Authors
  1. Zdenek Martinasek
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  2. Lukas Malina
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  3. Krisztina Trasy
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Corresponding author

Correspondence to Zdenek Martinasek .

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Editors and Affiliations

  1. Technical University of Sofia, Sofia, Bulgaria

    Nikos Mastorakis

  2. Departamentul de Inginerie Electrica, University of Craiova, Craiova, Romania

    Aida Bulucea

  3. Naval Academy, Piraeus, Greece

    George Tsekouras

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Martinasek, Z., Malina, L., Trasy, K. (2015). Profiling Power Analysis Attack Based on Multi-layer Perceptron Network. In: Mastorakis, N., Bulucea, A., Tsekouras, G. (eds) Computational Problems in Science and Engineering. Lecture Notes in Electrical Engineering, vol 343. Springer, Cham. https://doi.org/10.1007/978-3-319-15765-8_18

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  • DOI: https://doi.org/10.1007/978-3-319-15765-8_18

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-15764-1

  • Online ISBN: 978-3-319-15765-8

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