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SCA with Magnitude Squared Coherence

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Smart Card Research and Advanced Applications (CARDIS 2012)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 7771))

Abstract

Magnitude Squared Coherence (MSC) is a signal processing tool that indicates how well two time domain signals match one with the other by tracking linear dependencies in their spectral decomposition. Spectral Coherence ANalysis (SCAN) was the first way to use it as a Side-Channel Attack (SCA). This paper introduces two ways of using the Magnitude Squared Coherence in side-channel analyses. The first way is to use it as a distinguisher while the second consists in using it to transform the side-channel traces in a worthwhile manner. Additionally, an algorithm for fast computation of the SCAN is provided.

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References

  1. Bévan, R., Knudsen, E.: Ways to enhance differential power analysis. In: Lee, P.J., Lim, C.H. (eds.) ICISC 2002. LNCS, vol. 2587, pp. 327–342. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  2. Bohl, E., Hayek, J., Schimmel, O., Duplys, P., Rosenstiel, W.: Correlation power analysis in frequency domain. In: COSADE, Darmstadt, Germany (2010)

    Google Scholar 

  3. 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 

  4. Dehbaoui, A., Tiran, S., Maurine, P., Standaert, F.-X., Veyrat-Charvillon, N.: Spectral coherence analysis - first experimental results -. Cryptology ePrint Archive, Report 2011/056 (2011), http://eprint.iacr.org/

  5. Gebotys, C.H., Ho, S., Tiu, C.C.: EM Analysis of rijndael and ECC on a wireless java-based PDA. In: Rao, J.R., Sunar, B. (eds.) CHES 2005. LNCS, vol. 3659, pp. 250–264. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  6. Gierlichs, B., Batina, L., Tuyls, P., Preneel, B.: Mutual information analysis – A generic side-channel distinguisher. In: Oswald, E., Rohatgi, P. (eds.) CHES 2008. LNCS, vol. 5154, pp. 426–442. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  7. Kocher, P.C., Jaffe, J., Jun, B.: Differential power analysis. In: Wiener, M. (ed.) CRYPTO 1999. LNCS, vol. 1666, pp. 388–397. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  8. Mateos, E., Gebotys, C.H.: A new correlation frequency analysis of the side channel. In: WESS, p. 4 (2010)

    Google Scholar 

  9. Meynard, O., Réal, D., Guilley, S., Flament, F., Danger, J.-L., Valette, F.: Characterization of the electromagnetic side channel in frequency domain. In: Lai, X., Yung, M., Lin, D. (eds.) Inscrypt 2010. LNCS, vol. 6584, pp. 471–486. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  10. Welch, P.D.: The use of fast fourier transform for the estimation of power spectra: A method based on time averaging over short. IEEE Trans. Audio Electroacoustics 15, 70–73 (1967)

    Article  MathSciNet  Google Scholar 

  11. Standaert, F.-X., Gierlichs, B., Verbauwhede, I.: Partition vs. Comparison side-channel distinguishers: An empirical evaluation of statistical tests for univariate side-channel attacks against two unprotected CMOS devices. In: Lee, P.J., Cheon, J.H. (eds.) ICISC 2008. LNCS, vol. 5461, pp. 253–267. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  12. 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 

  13. Tiran, S., Dehbaoui, A., Maurine, P.: Magnitude squared coherence based SCA. Cryptology ePrint Archive, Report 2012/077 (2012), http://eprint.iacr.org/

  14. Veyrat-Charvillon, N., Standaert, F.-X.: Mutual information analysis: How, when and why? In: Clavier, C., Gaj, K. (eds.) CHES 2009. LNCS, vol. 5747, pp. 429–443. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  15. Whitnall, C., Oswald, E., Mather, L.: An exploration of the kolmogorov-smirnov test as a competitor to mutual information analysis. In: Prouff, E. (ed.) CARDIS 2011. LNCS, vol. 7079, pp. 234–251. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

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Tiran, S., Maurine, P. (2013). SCA with Magnitude Squared Coherence. In: Mangard, S. (eds) Smart Card Research and Advanced Applications. CARDIS 2012. Lecture Notes in Computer Science, vol 7771. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37288-9_16

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  • DOI: https://doi.org/10.1007/978-3-642-37288-9_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37287-2

  • Online ISBN: 978-3-642-37288-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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