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Enhanced Correlation Power Analysis by Biasing Power Traces

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Information Security (ISC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 9866))

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Abstract

Biasing power traces with high Signal to Noise Ratio (SNR) proposed by K. Yongdae et al. can significantly improve the efficiency of the CPA. But it is still a problem to be solved that how to efficiently select power traces with high SNR. Through the analysis of the statistical characteristics of power traces, we propose three methods to better solve this problem in this paper. We bias power traces by using the Minkowski distance (i.e. Euclidean distance or Manhattan distance) between each power trace and mean power trace. Biasing power traces can also be carried out by using probability density function values of power consumption of interesting points, or even directly using power consumption of interesting points. Our schemes can blindly select power traces with high SNR in a high probability. The efficiency of the CPA by using the three of our methods is significantly improved. Thus, our schemes are more effective compared to the one proposed by K. Yongdae et al.

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References

  1. Agrawal, D., Archambeault, B., Rao, J.R., Rohatgi, P.: The EM side—channel(s). In: Kaliski Jr., B.S., Koç, Ç.K., Paar, C. (eds.) CHES 2002. LNCS, vol. 2523. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  2. Agrawal, D., Rao, J.R., Rohatgi, P., Schramm, K.: Templates as master keys. In: Rao, J.R., Sunar, B. (eds.) CHES 2005. LNCS, vol. 3659, pp. 15–29. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  3. Becker, G.T., Kasper, M., Moradi, A., Paar, C.: Side-channel based watermarks for integrated circuits. In: IEEE International Symposium on Hardware-Oriented Security and Trust, pp. 30–35 (2010)

    Google Scholar 

  4. Benhadjyoussef, N., Machhout, M., Tourki, R.: Optimized power trace numbers in CPA attacks. In: 2011 8th International Multi-Conference on Systems, Signals and Devices (SSD), pp. 1–5 (2011)

    Google Scholar 

  5. Bohy, L., Neve, M., Samyde, D., Quisquater, J.J.: Principal and independent component analysis for crypto-systems with hardware unmasked units. In: Proceedings of e-Smart 2003 (2003)

    Google Scholar 

  6. Brier, E., Clavier, C., Olivier, F.: Correlation power analysis with a leakage model. In: Joye, M., Quisquater, J.-J. (eds.) CHES 2004. LNCS, vol. 3156, pp. 16–29. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  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. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  8. Genkin, D., Shamir, A., Tromer, E.: Acoustic cryptanalysis. J. Cryptol. 1–52 (2016). doi:10.1007/s00145-015-9224-2

    Google Scholar 

  9. Gierlichs, B., Batina, L., Tuyls, P., Preneel, B.: Mutual information analysis. In: Oswald, E., Rohatgi, P. (eds.) CHES 2008. LNCS, vol. 5154, pp. 426–442. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  10. Hu, W., Wu, L., Wang, A., Xie, X., Zhu, Z., Luo, S.: Adaptive chosen-plaintext correlation power analysis. In: Tenth International Conference on Computational Intelligence and Security, pp. 494–498 (2014)

    Google Scholar 

  11. Kim, Y., Sugawara, T., Homma, N., Aoki, T., Satoh, A.: Biasing power traces to improve correlation in power analysis attacks. ESRC Centre Population Change 2(3), 10–16 (2014)

    Google Scholar 

  12. Kocher, P., Jaffe, J., Jun, B.: Differential power analysis. Int. Cryptol. Conf. Adv. Cryptol. 1666, 388–397 (1999)

    Article  MATH  Google Scholar 

  13. Kocher, P.C.: Timing attacks on implementations of Diffie-Hellman, RSA, DSS, and other systems. Int. Cryptol. Conf. Adv. Cryptol. 1109, 104–113 (2010)

    MATH  Google Scholar 

  14. Mangard, S., Oswald, E., Popp, T.: Power Analysis Attacks: Revealing the Secrets of Smart Cards. Springer, New York (2007)

    MATH  Google Scholar 

  15. 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)

    Chapter  Google Scholar 

  16. Schramm, K., Wollinger, T., Paar, C.: A new class of collision attacks and its application to DES. Fast Softw. Encryp. FSE 2887(6), 206–222 (2003)

    Article  MATH  Google Scholar 

  17. 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)

    Chapter  Google Scholar 

  18. 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)

    Chapter  Google Scholar 

  19. Tiri, K., Schaumont, P.: Changing the odds against masked logic. In: Biham, E., Youssef, A.M. (eds.) SAC 2006. LNCS, vol. 4356, pp. 134–146. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

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Acknowledgment

This research is supported by the Nation Natural Science Foundation of China (No. 61372062). The authors would like to thank the anonymous referees of ISC 2016 for the suggestions to improve this paper.

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Authors and Affiliations

  1. Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China

    Changhai Ou, Zhu Wang, Degang Sun, Xinping Zhou, Juan Ai & Na Pang

  2. University of Chinese Academy of Sciences, Beijing, China

    Changhai Ou, Xinping Zhou, Juan Ai & Na Pang

Authors
  1. Changhai Ou
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  2. Zhu Wang
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  3. Degang Sun
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  4. Xinping Zhou
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  5. Juan Ai
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  6. Na Pang
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Corresponding authors

Correspondence to Changhai Ou or Zhu Wang .

Editor information

Editors and Affiliations

  1. University of California , Davies, USA

    Matt Bishop

  2. University of Washington , Tacoma, Washington, USA

    Anderson C A Nascimento

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Ou, C., Wang, Z., Sun, D., Zhou, X., Ai, J., Pang, N. (2016). Enhanced Correlation Power Analysis by Biasing Power Traces. In: Bishop, M., Nascimento, A. (eds) Information Security. ISC 2016. Lecture Notes in Computer Science(), vol 9866. Springer, Cham. https://doi.org/10.1007/978-3-319-45871-7_5

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  • DOI: https://doi.org/10.1007/978-3-319-45871-7_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45870-0

  • Online ISBN: 978-3-319-45871-7

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