Composable Masking Schemes in the Presence of Physical Defaults & the Robust Probing Model

Faust, Sebastian;Grosso, Vincent;Merino Del Pozo, Santos;Paglialonga, Clara;Standaert, François-Xavier
(2018) IACR Transactions on Cryptographic Hardware and Embedded Systems — Vol. 2018, n° 3, p. 89-120 (2018)

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Authors
  • Faust, SebastianTechnische Universität Darmstadt, Darmstadt/Germany
    Author
  • Grosso, VincentRadboud University Nijmegen, Digital Security Group/The Netherlands
    Author
  • Merino Del Pozo, SantosUCLouvain
    Author
  • Paglialonga, ClaraTechnische Universität Darmstadt, Darmstadt/Germany
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Abstract
Composability and robustness against physical defaults (e.g., glitches) are two highly desirable properties for secure implementations of masking schemes. While tools exist to guarantee them separately, no current formalism enables their joint investigation. In this paper, we solve this issue by introducing a new model, the robust probing model, that is naturally suited to capture the combination of these properties. We first motivate this formalism by analyzing the excellent robustness and low randomness requirements of first-order threshold implementations, and highlighting the difficulty to extend them to higher orders. Next, and most importantly, we use our theory to design and prove the first higher-order secure, robust and composable multiplication gadgets. While admittedly inspired by existing approaches to masking (e.g., Ishai-Sahai-Wagner-like, threshold, domain-oriented), these gadgets exhibit subtle implementation differences with these state-of-the-art solutions (none of which being provably composable and robust). Hence, our results illustrate how sound theoretical models can guide practically-relevant implementations.
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Citations

Faust, S., Grosso, V., Merino Del Pozo, S., Paglialonga, C., & Standaert, F.-X. (2018). Composable Masking Schemes in the Presence of Physical Defaults & the Robust Probing Model. IACR Transactions on Cryptographic Hardware and Embedded Systems, 2018(3), 89-120. https://doi.org/10.13154/tches.v2018.i3.89-120 (Original work published 2018)