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International Conference on Smart Card Research and Advanced Applications

CARDIS 2016: Smart Card Research and Advanced Applications pp 209–227Cite as

PRNGs for Masking Applications and Their Mapping to Evolvable Hardware

Part of the Lecture Notes in Computer Science book series (LNSC,volume 10146)

Abstract

This paper proposes the use of evolutionary computation for the design and optimization of lightweight Pseudo Random Number Generators (PRNGs). In this work, we focus on PRNGs that are suitable for generating masks and secret shares. Such generators should be light-weight and have a high throughput with good statistical properties. As a proof-of-concept, we present three novel hardware architectures that have an increasing level of prediction resistance and an increasing level of reconfigurability at run-time. We evaluate the three architectures on Zynq, Virtex-6, and ASIC platforms and compare the occupied resources and the throughput of the obtained designs. Finally, we use the Spartan-6 platform for the evaluation of the masked implementation where the masks are obtained via our PRNG.

Keywords

  • Block Cipher
  • Hardware Architecture
  • Modeling Attack
  • Embed Processor
  • Cartesian Genetic Programming

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This work has been supported in part by Croatian Science Foundation under the project IP-2014-09-4882. In addition, this work was supported in part by the Research Council KU Leuven (C16/15/058), (CREA/14/005), and CORNET project DynamIA (IWT 140389). It was also supported in part by the Flemish Government through G.0130.13N and FWO G.0876.14N, the Hercules Foundation AKUL/11/19, and through the Cathedral ERC Advanced Grant 695305.

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Authors and Affiliations

  1. KU Leuven ESAT/COSIC and imec, Kasteelpark Arenberg 10, 3001, Leuven-Heverlee, Belgium

    Stjepan Picek, Bohan Yang, Vladimir Rozic, Jo Vliegen, Jori Winderickx, Thomas De Cnudde & Nele Mentens

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  1. Stjepan Picek
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  2. Bohan Yang
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  3. Vladimir Rozic
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  4. Jo Vliegen
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Correspondence to Stjepan Picek .

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Editors and Affiliations

  1. Bonn-Rhein-Sieg University of Applied Sciences, St. Augustin, Germany

    Kerstin Lemke-Rust

  2. Cryptography Research Inc. , San Francisco, California, USA

    Michael Tunstall

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Picek, S. et al. (2017). PRNGs for Masking Applications and Their Mapping to Evolvable Hardware. In: Lemke-Rust, K., Tunstall, M. (eds) Smart Card Research and Advanced Applications. CARDIS 2016. Lecture Notes in Computer Science(), vol 10146. Springer, Cham. https://doi.org/10.1007/978-3-319-54669-8_13

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