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Efficient Template Attacks

  • Omar Choudary
  • Markus G. Kuhn
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8419)

Abstract

Template attacks remain a powerful side-channel technique to eavesdrop on tamper-resistant hardware. They model the probability distribution of leaking signals and noise to guide a search for secret data values. In practice, several numerical obstacles can arise when implementing such attacks with multivariate normal distributions. We propose efficient methods to avoid these. We also demonstrate how to achieve significant performance improvements, both in terms of information extracted and computational cost, by pooling covariance estimates across all data values. We provide a detailed and systematic overview of many different options for implementing such attacks. Our experimental evaluation of all these methods based on measuring the supply current of a byte-load instruction executed in an unprotected 8-bit microcontroller leads to practical guidance for choosing an attack algorithm.

Keywords

Side-channel attacks Template attack Multivariate analysis 

Notes

Acknowledgement

Omar Choudary is a recipient of the Google Europe Fellowship in Mobile Security, and this research is supported in part by this Google Fellowship. The opinions expressed in this paper do not represent the views of Google unless otherwise explicitly stated.

Supplementary material

References

  1. 1.
    Mahalanobis, P.C.: On the generalised distance in statistics. In: Proceedings National Institute of Science, India, vol. 2, pp. 49–55 (1936)Google Scholar
  2. 2.
    Fisher, R.A.: The statistical utilization of multiple measurements. Ann. Eugen. 8, 376–386 (1938)CrossRefGoogle Scholar
  3. 3.
    Box, G.E.P.: Problems in the analysis of growth and wear curves. Biometrics 6, 362–389 (1950)CrossRefGoogle Scholar
  4. 4.
    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. 51–62. Springer, Heidelberg (2003) CrossRefGoogle Scholar
  5. 5.
    Ledoit, O., Wolf, M.: A well-conditioned estimator for large-dimensional covariance matrices. J. Multivar. Anal. 88, 365–411 (2004)CrossRefzbMATHMathSciNetGoogle Scholar
  6. 6.
    Jolliffe, I.: Principal Component Analysis. Wiley, Chichester (2005)Google Scholar
  7. 7.
    Rechberger, C., Oswald, E.: Practical template attacks. In: Lim, C.H., Yung, M. (eds.) WISA 2004. LNCS, vol. 3325, pp. 440–456. Springer, Heidelberg (2005) CrossRefGoogle Scholar
  8. 8.
    Archambeau, C., Peeters, E., Standaert, F.-X., Quisquater, J.-J.: Template attacks in principal subspaces. In: Goubin, L., Matsui, M. (eds.) CHES 2006. LNCS, vol. 4249, pp. 1–14. Springer, Heidelberg (2006) CrossRefGoogle Scholar
  9. 9.
    Gierlichs, B., Lemke-Rust, 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
  10. 10.
    Johnson, R., Wichern, D.: Applied Multivariate Statistical Analysis, 6th edn. Pearson, Upper Saddle River (2007)zbMATHGoogle Scholar
  11. 11.
    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
  12. 12.
    Batina, L., Gierlichs, B., Lemke-Rust, K.: Comparative evaluation of rank correlation based DPA on an AES prototype chip. In: Wu, T.-C., Lei, C.-L., Rijmen, V., Lee, D.-T. (eds.) ISC 2008. LNCS, vol. 5222, pp. 341–354. Springer, Heidelberg (2008) CrossRefGoogle Scholar
  13. 13.
    Standaert, F.-X., Malkin, T.G., Yung, M.: A unified framework for the analysis of side-channel key recovery attacks. In: Joux, A. (ed.) EUROCRYPT 2009. LNCS, vol. 5479, pp. 443–461. Springer, Heidelberg (2009) CrossRefGoogle Scholar
  14. 14.
    Eisenbarth, T., Paar, C., Weghenkel, B.: Building a side channel based disassembler. Trans. Comput. Sci. X 6340, 78–99 (2010)CrossRefMathSciNetGoogle Scholar
  15. 15.
    Mangard, S., Oswald, E., Popp, T.: Power Analysis Attacks: Revealing the Secrets of Smart Cards, 1st edn. Springer, Heidelberg (2010)Google Scholar
  16. 16.
    Oswald, D., Paar, C.: Breaking Mifare DESFire MF3ICD40: power analysis and templates in the real world. In: Preneel, B., Takagi, T. (eds.) CHES 2011. LNCS, vol. 6917, pp. 207–222. Springer, Heidelberg (2011) CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Computer LaboratoryUniversity of CambridgeCambridgeUK

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