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Binary Data Analysis for Source Code Leakage Assessment

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Abstract

Side Channel Analysis (SCA) is known to be a serious threat for cryptographic algorithms since twenty years. Recently, the explosion of the Internet of Things (IoT) has increased the number of devices that can be targeted by these attacks, making this threat more relevant than ever. Furthermore, the evaluations of cryptographic algorithms regarding SCA are usually performed at the very end of a product design cycle, impacting considerably the time-to-market in case of security flaws. Hence, early simulations of embedded software and methodologies have been developed to assess vulnerabilities with respect to SCA for specific hardware architectures. Aiming to provide an agnostic evaluation method, we propose in this paper a new methodology of data collection and analysis to reveal leakage of sensitive information from any software implementation. As an illustration our solution is used interestingly to break a White Box Cryptography (WBC) implementation, challenging existing simulation-based attacks.

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Acknowledgments

This work was partly supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No. 2016-0-00399, Study on secure key hiding technology for IoT devices [KeyHAS Project]) and other project(s).

Author information

Authors and Affiliations

  1. Secure-IC S.A.S, Rennes, France

    Adrien Facon, Sylvain Guilley, Matthieu Lec’hvien, Damien Marion & Thomas Perianin

  2. Telecom ParisTech, Institut Mines-Télécom, Paris, France

    Sylvain Guilley & Damien Marion

  3. École Normale Supérieure, Paris, France

    Adrien Facon & Sylvain Guilley

Authors
  1. Adrien Facon

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  2. Sylvain Guilley

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  3. Matthieu Lec’hvien

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  4. Damien Marion

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  5. Thomas Perianin

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Corresponding author

Correspondence toDamien Marion.

Editor information

Editors and Affiliations

  1. Inria-RBA, Rennes, France

    Jean-Louis Lanet

  2. Bucharest University of Economic Studies, Bucharest, Romania

    Cristian Toma

Appendix

Appendix

Table 2. Leakage characterization and mapping to the source code

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Facon, A., Guilley, S., Lec’hvien, M., Marion, D., Perianin, T. (2019). Binary Data Analysis for Source Code Leakage Assessment. In: Lanet, JL., Toma, C. (eds) Innovative Security Solutions for Information Technology and Communications. SECITC 2018. Lecture Notes in Computer Science(), vol 11359. Springer, Cham. https://doi.org/10.1007/978-3-030-12942-2_30

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