Advertisement

How to Compare Profiled Side-Channel Attacks?

  • François-Xavier Standaert
  • François Koeune
  • Werner Schindler
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5536)

Abstract

Side-channel attacks are an important class of attacks against cryptographic devices and profiled side-channel attacks are the most powerful type of side-channel attacks. In this scenario, an adversary first uses a device under his control in order to build a good leakage model. Then, he takes advantage of this leakage model to exploit the actual leakages of a similar target device and perform a key recovery. Since such attacks are divided in two phases (namely profiling and online attack), the question of how to best evaluate those two phases arises. In this paper, we take advantage of a recently introduced framework for the analysis of side-channel attacks to tackle this issue. We show that the quality of a profiling phase is nicely captured by an information theoretic metric. By contrast, the effectiveness of the online key recovery phase is better measured with a security metric. As an illustration, we use this methodology to compare the two main techniques for profiled side-channel attacks, namely template attacks and stochastic models. Our results confirm the higher profiling efficiency of stochastic models when reasonable assumptions can be made about the leakages of a device.

Keywords

Stochastic Model Block Cipher Conditional Entropy Target Device Leakage Model 
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.

References

  1. 1.
    Chari, S., Rao, J., Rohatgi, P.: Template Attacks. In: Kaliski Jr., B.S., Koç, Ç.K., Paar, C. (eds.) CHES 2002. LNCS, vol. 2523, pp. 13–28. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  2. 2.
    Gierlichs, B., Lemke, K., Paar, C.: Templates vs. Stochastic Methods. In: Goubin, L., Matsui, M. (eds.) CHES 2006. LNCS, vol. 4249, pp. 15–29. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  3. 3.
    Lemke, K., Paar, C.: Analyzing Side-Channel Leakage of Masked Implementations with Stochastic Methods. In: Biskup, J., López, J. (eds.) ESORICS 2007. LNCS, vol. 4734, pp. 454–468. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  4. 4.
    Mangard, S., Oswald, E., Popp, T.: Power Analysis Attacks. Springer, Heidelberg (2007)zbMATHGoogle Scholar
  5. 5.
    Schindler, W., Lemke, K., Paar, C.: A stochastic model for differential side channel cryptanalysis. In: Rao, J.R., Sunar, B. (eds.) CHES 2005. LNCS, vol. 3659, pp. 30–46. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  6. 6.
    Schindler, W.: Advanced Stochastic Methods in Side-Channel Analysis on Block Ciphers in the Presence of Masking. J. of Math. Cryptology 2, 291–310 (2008)MathSciNetCrossRefzbMATHGoogle Scholar
  7. 7.
    Standaert, F.-X., Malkin, T.G., Yung, M.: A Unified Framework for the Analysis of Side-Channel Key Recovery Attacks. To appear in the proceedings of Eurocrypt (2009); Extended version available from: Cryptology ePrint Archive, Report 2006/139Google Scholar
  8. 8.
    Standaert, F.-X., Peeters, E., Archambeau, C., Quisquater, J.-J.: Towards Security Limits in Side-Channel Attacks. In: Goubin, L., Matsui, M. (eds.) CHES 2006. LNCS, vol. 4249, pp. 30–45. Springer, Heidelberg (2006), http://eprint.iacr.org/2007/222 CrossRefGoogle Scholar
  9. 9.
    Standaert, F.-X., Archambeau, C.: Using Subspace-Based Template Attacks to Compare and Combine Power and Electromagnetic Information Leakages. In: Oswald, E., Rohatgi, P. (eds.) CHES 2008. LNCS, vol. 5154, pp. 411–425. Springer, Heidelberg (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • François-Xavier Standaert
    • 1
  • François Koeune
    • 1
  • Werner Schindler
    • 2
  1. 1.UCL Crypto GroupUniversité catholique de LouvainLouvain-la-NeuveBelgium
  2. 2.Bundesamt für Sicherheit in der Informationstecknik (BSI)BonnGermany

Personalised recommendations