Taylor Expansion of Maximum Likelihood Attacks for Masked and Shuffled Implementations

Bruneau, Nicolas;Guilley, Sylvain;Heuser, Annelie;Rioul, Olivier;Teglia, Yannick;et.al.
(2016) 22nd International Conference on the Theory and Application of Cryptology and Information Security (ASIACRYPT 2016) — Location: Hanoi (Vietnam) (4.December.2016)

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Authors
  • Bruneau, NicolasInstitut Mines-Télécom, Télécom ParisTech/France
    Author
  • Guilley, SylvainInstitut Mines-Télécom, Télécom ParisTech/France
    Author
  • Heuser, AnnelieInstitut Mines-Télécom, Télécom ParisTech/France
    Author
  • Rioul, OlivierInstitut Mines-Télécom, Télécom ParisTech/France
    Author
  • Standaert, François-XavierUCLouvain
    Author
  • Teglia, YannickGemalto, Security Labs, La Ciotat/France
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Abstract
The maximum likelihood side-channel distinguisher of a template attack scenario is expanded into lower degree attacks according to the increasing powers of the signal-to-noise ratio (SNR). By exploiting this decomposition we show that it is possible to build highly multivariate attacks which remain efficient when the likelihood cannot be computed in practice due to its computational complexity. The shuffled table recomputation is used as an illustration to derive a new attack which outperforms the ones presented by Bruneau et al. at CHES 2015, and so across the full range of SNRs. This attack combines two attack degrees and is able to exploit high dimensional leakage which explains its efficiency.
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Bruneau, N., Guilley, S., Heuser, A., Rioul, O., Standaert, F.-X., & Teglia, Y. (2016). Taylor Expansion of Maximum Likelihood Attacks for Masked and Shuffled Implementations. In Junhg Hee Cheon, Tsuyoshi Takagi (ed.), Proceedings of the 22nd International Conference on the Theory and Application of Cryptology and Information Security (ASIACRYPT 2016) (p. p. 573-601). Springer. https://doi.org/10.1007/978-3-662-53887-6_21