Defensive leakage camouflage

  • Authors:
  • Eric Brier;Fortier Quentin;Roman Korkikian;K. W. Magld;David Naccache;Guilherme Ozari de Almeida;Adrien Pommellet;A. H. Ragab;Jean Vuillemin

  • Affiliations:
  • Ingenico, Guilherand-Granges, France;Département d'informatique, École normale supérieure, Paris Cedex 05, France;Altis Semiconductor, Corbeil-Essonnes, France, Sorbonne Universités --- Université Paris II, Paris Cedex 05, France;King Abdulaziz University, Jeddah, Saudi Arabia;Département d'informatique, École normale supérieure, Paris Cedex 05, France, Sorbonne Universités --- Université Paris II, Paris Cedex 05, France;Altis Semiconductor, Corbeil-Essonnes, France, Sorbonne Universités --- Université Paris II, Paris Cedex 05, France;Département d'informatique, École normale supérieure, Paris Cedex 05, France;King Abdulaziz University, Jeddah, Saudi Arabia;Département d'informatique, École normale supérieure, Paris Cedex 05, France, King Abdulaziz University, Jeddah, Saudi Arabia

  • Venue:
  • CARDIS'12 Proceedings of the 11th international conference on Smart Card Research and Advanced Applications
  • Year:
  • 2012

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Abstract

This paper considers the transfer of digital data over leaky and noisy communication channels. We develop defensive strategies exploiting the fact that noise prevents the attacker from accurately measuring leakage. The defense strategy described in this paper pairs each useful data element k with a camouflage value v and simultaneously transmits both k and v over the channel. This releases an emission e(k,v). We wish to select the camouflage values v(k) as a function of k in a way that makes the quantities e(k,v(k)) as indistinguishable as possible from each other. We model the problem and show that optimal camouflage values can be computed from side-channels under very weak physical assumptions. The proposed technique is hence applicable to a wide range of readily available technologies. We propose algorithms for computing optimal camouflage values when the number of samples per trace is moderate (typically ≤6) and justify our models by a statistical analysis. We also provide experimental results obtained using FPGAs.