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Taylor Expansion of Maximum Likelihood Attacks for Masked and Shuffled Implementations

  • Nicolas Bruneau
  • Sylvain Guilley
  • Annelie Heuser
  • Olivier Rioul
  • François-Xavier Standaert
  • Yannick Teglia
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10031)

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.

Keywords

Template attacks Taylor expansion Shuffled table recomputation 

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Copyright information

© International Association for Cryptologic Research 2016

Authors and Affiliations

  • Nicolas Bruneau
    • 1
    • 2
  • Sylvain Guilley
    • 1
    • 3
  • Annelie Heuser
    • 1
  • Olivier Rioul
    • 1
  • François-Xavier Standaert
    • 4
  • Yannick Teglia
    • 5
  1. 1.Institut Mines-Télécom, Télécom ParisTech, CNRS LTCI Department ComelecParisFrance
  2. 2.STMicroelectronics, AST DivisionRoussetFrance
  3. 3.Secure-IC S.A.S.RennesFrance
  4. 4.ICTEAM/ELEN/Crypto GroupUniversité catholique de LouvainLouvain-la-NeuveBelgium
  5. 5.Gemalto, Security LabsLa CiotatFrance

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