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Improved EM Side-Channel Authentication Using Profile-Based XOR Model

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Information Security Applications (WISA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 10763))

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Abstract

A new approach for authentication, side-channel authentication, has been proposed. In side-channel authentication, the authenticity of the device is confirmed with high accuracy by using electromagnetic radiation from the device and response in the conventional challenge–response authentication. The side-channel model or profiled template is used as one of the inputs of the distinguisher when authenticated. The performance of side-channel authentication is greatly affected by the precision of the model or template. In this paper, we evaluate the authentication performance when using profile- and non-profile-based HD models and a profile-based XOR model. We report the results of the experiment in detail using FPGA.

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Notes

  1. 1.

    AES can be replaced with other symmetric-key ciphers.

  2. 2.

    The intermediate values influenced by a biased plaintext are not used.

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Acknowledgments

This work was supported by Japan Society for the Promotion of Science (JSPS) Grants-in-Aid for Scientific Research (KAKENHI) Grant Numbers 15K12035.

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Authors and Affiliations

  1. Department of Informatics, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo, 182-8585, Japan

    Momoka Kasuya & Kazuo Sakiyama

Authors
  1. Momoka Kasuya
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  2. Kazuo Sakiyama
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Corresponding author

Correspondence to Momoka Kasuya .

Editor information

Editors and Affiliations

  1. KAIST, Daejeon, Korea (Republic of)

    Brent ByungHoon Kang

  2. Georgia Institute of Technology, Atlanta, Georgia, USA

    Taesoo Kim

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Kasuya, M., Sakiyama, K. (2018). Improved EM Side-Channel Authentication Using Profile-Based XOR Model. In: Kang, B., Kim, T. (eds) Information Security Applications. WISA 2017. Lecture Notes in Computer Science(), vol 10763. Springer, Cham. https://doi.org/10.1007/978-3-319-93563-8_15

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  • DOI: https://doi.org/10.1007/978-3-319-93563-8_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-93562-1

  • Online ISBN: 978-3-319-93563-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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