Advertisement

Formally Bounding the Side-Channel Leakage in Unknown-Message Attacks

  • Michael Backes
  • Boris Köpf
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5283)

Abstract

We propose a novel approach for quantifying a system’s resistance to unknown-message side-channel attacks. The approach is based on a measure of the secret information that an attacker can extract from a system from a given number of side-channel measurements. We provide an algorithm to compute this measure, and we use it to analyze the resistance of hardware implementations of cryptographic algorithms with respect to timing attacks. In particular, we show that message-blinding – the common countermeasure against timing attacks – reduces the rate at which information about the secret is leaked, but that the complete information is still eventually revealed. Finally, we compare information measures corresponding to unknown-message, known-message, and chosen-message attackers and show that they form a strict hierarchy.

Keywords

Timing Attack Conditional Entropy Secret Information Attack Scenario Attack Strategy 
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.
    Backes, M., Köpf, B.: Formally Bounding the Side-Channel Leakage in Unknown-Message Attacks. Cryptology ePrint Archive, Report 2008/162 (2008)Google Scholar
  2. 2.
    Batu, T., Dasgupta, S., Kumar, R., Rubinfeld, R.: The complexity of approximating entropy. In: Proc. STOC 2002, pp. 678–687. ACM, New York (2002)Google Scholar
  3. 3.
    Bird, R.: Introduction to Functional Programming using Haskell, 2nd edn. Prentice Hall, Englewood Cliffs (1998)Google Scholar
  4. 4.
    Boneh, D., Brumley, D.: Remote Timing Attacks are Practical. In: Proc. USENIX Security Symposium 2003 (2003)Google Scholar
  5. 5.
    Cachin, C.: Entropy Measures and Unconditional Security in Cryptography. Ph.D thesis, ETH Zürich (1997)Google Scholar
  6. 6.
    Chari, S., Jutla, C.S., Rao, J.R., Rohatgi, P.: Towards Sound Approaches to Counteract Power-Analysis Attacks. In: Wiener, M. (ed.) CRYPTO 1999. LNCS, vol. 1666, pp. 398–412. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  7. 7.
    Chari, S., Rao, J.R., 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
  8. 8.
    Clark, D., Hunt, S., Malacaria, P.: Quantitative Information Flow, Relations and Polymorphic Types. J. Log. Comput. 18(2), 181–199 (2005)MathSciNetCrossRefzbMATHGoogle Scholar
  9. 9.
    Clarkson, M., Myers, A., Schneider, F.: Belief in Information Flow. In: Proc. CSFW 2005, pp. 31–45. IEEE, Los Alamitos (2005)Google Scholar
  10. 10.
    Davio, M., Deschamps, J.P., Thayse, A.: Digital Systems with Algorithm Implementation. John Wiley & Sons, Inc., Chichester (1983)zbMATHGoogle Scholar
  11. 11.
    Gandolfi, K., Mourtel, C., Olivier, F.: Electromagnetic analysis: Concrete results. In: Koç, Ç.K., Naccache, D., Paar, C. (eds.) CHES 2001. LNCS, vol. 2162, pp. 251–261. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  12. 12.
    Kocher, P.: Timing Attacks on Implementations of Diffie-Hellman, RSA, DSS, and Other Systems. In: Koblitz, N. (ed.) CRYPTO 1996. LNCS, vol. 1109, pp. 104–113. Springer, Heidelberg (1996)Google Scholar
  13. 13.
    Kocher, P., Jaffe, J., Jun, B.: Differential Power Analysis. In: Wiener, M. (ed.) CRYPTO 1999. LNCS, vol. 1666, pp. 388–397. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  14. 14.
    Köpf, B., Basin, D.: An Information-Theoretic Model for Adaptive Side-Channel Attacks. In: Proc. CCS 2007, pp. 286–296. ACM, New York (2007)Google Scholar
  15. 15.
    Lowe, G.: Quantifying Information Flow. In: Proc. CSFW 2002, pp. 18–31. IEEE, Los Alamitos (2002)Google Scholar
  16. 16.
    Mace, F., Standaert, F.-X., Quisquater, J.-J.: An Informtion Theoretic Evaluation of Side-Channel Resistant Logic Styles. In: Paillier, P., Verbauwhede, I. (eds.) CHES 2007. LNCS, vol. 4727, pp. 427–442. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  17. 17.
    Mangard, S., Oswald, E., Popp, T.: Power Analysis Attacks: Revealing the Secrets of Smart Cards. Springer, Heidelberg (2007)zbMATHGoogle Scholar
  18. 18.
    Massey, J.L.: Guessing and Entropy. In: Proc. IEEE Int. Symp. on Info. Th. 1994, p. 204. IEEE, Los Alamitos (1994)CrossRefGoogle Scholar
  19. 19.
    Menezes, A., van Oorschot, P., Vanstone, S.: Handbook of Applied Cryptography. CRC Press, Boca Raton (1996)CrossRefzbMATHGoogle Scholar
  20. 20.
    Messerges, T.S., Dabbish, E.A., Sloan, R.H.: Power Analysis Attacks of Modular Exponentiation in Smartcards. In: Koç, Ç.K., Paar, C. (eds.) CHES 1999. LNCS, vol. 1717, pp. 144–157. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  21. 21.
    Micali, S., Reyzin, L.: Physically Observable Cryptography (Extended Abstract). In: Naor, M. (ed.) TCC 2004. LNCS, vol. 2951, pp. 278–296. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  22. 22.
    Osvik, D.A., Shamir, A., Tromer, E.: Cache Attacks and Countermeasures: the Case of AES. In: Pointcheval, D. (ed.) CT-RSA 2006. LNCS, vol. 3860, pp. 1–20. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  23. 23.
    Petit, C., Standaert, F.-X., Pereira, O., Malkin, T.G., Yung, M.: A Block Cipher based Pseudo Random Number Generator Secure Against Side-Channel Key Recovery. In: Proc. AsiaCCS 2008, pp. 56–65. ACM, New York (2008)Google Scholar
  24. 24.
    Quisquater, J.-J., Samyde, D.: ElectroMagnetic Analysis (EMA): Measures and Couter-Measures for Smard Cards. In: Attali, S., Jensen, T. (eds.) E-smart 2001. LNCS, vol. 2140, pp. 200–210. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  25. 25.
    Schaumont, P., Ching, D., Verbauwhede, I.: An Interactive Codesign Environment for Domain-Specific Coprocessors. ACM Transactions on Design Automation for Electronic Systems 11(1), 70–87 (2006)CrossRefGoogle Scholar
  26. 26.
    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)CrossRefGoogle Scholar
  27. 27.
    Standaert, F.-X., Malkin, T.G., Yung, M.: A Unified Framework for the Analysis of Side-Channel Key Recovery Attacks. Cryptology ePrint Archive, Report 2006/139 (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Michael Backes
    • 1
    • 2
  • Boris Köpf
    • 2
  1. 1.Saarland UniversityGermany
  2. 2.MPI-SWSGermany

Personalised recommendations