Abstract
Template attacks are widely accepted to be the most powerful side-channel attacks from an information theoretic point of view. For template attacks to be practical, one needs to choose some special samples as the interesting points in actual power traces. Up to now, many different approaches were introduced for choosing interesting points for template attacks. However, it is unknown that whether or not the previous approaches of choosing interesting points will lead to the best classification performance of template attacks. In this work, we give a negative answer to this important question by introducing a practical new approach which has completely different basic principle compared with all the previous approaches. Our new approach chooses the point whose distribution of samples approximates to a normal distribution as the interesting point. Evaluation results exhibit that template attacks based on the interesting points chosen by our new approach can achieve obvious better classification performance compared with template attacks based on the interesting points chosen by the previous approaches. Therefore, our new approach of choosing interesting points should be used in practice to better understand the practical threats of template attacks.
Keywords
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
The points \(P_0,\ldots ,P_3\) are in the first clock cycle. The points \(P_4,\ldots ,P_7\) are in the second clock cycle. The points \(P_8,\ldots ,P_{11}\) are in the third clock cycle. The points \(P_{12},\ldots ,P_{15}\) are in the fourth clock cycle.
References
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)
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)
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)
Choudary, O., Kuhn, M.G.: Efficient template attacks. In: Francillon, A., Rohatgi, P. (eds.) CARDIS 2013. LNCS, vol. 8419, pp. 253–270. Springer, Heidelberg (2014)
Bär, M., Drexler, H., Pulkus, J.: Improved template attacks. In: COSADE2010 (2010)
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)
Montminy, D.P., Baldwin, R.O., Temple, M.A., Laspe, E.D.: Improving cross-device attacks using zero-mean unit-variance mormalization. J. Cryptographic Eng. 3(2), 99–110 (2013)
Oswald, E., Mangard, S.: Template attacks on masking—resistance is futile. In: Abe, M. (ed.) CT-RSA 2007. LNCS, vol. 4377, pp. 243–256. Springer, Heidelberg (2006)
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)
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)
Mangard, S., Oswald, E., Popp, T.: Power Analysis Attacks: Revealing the Secrets of Smart Cards. Springer, Berlin (2007)
Hanley, N., Tunstall, M., Marnane, W.P.: Unknown plaintext template attacks. In: Youm, H.Y., Yung, M. (eds.) WISA 2009. LNCS, vol. 5932, pp. 148–162. Springer, Heidelberg (2009)
Durvaux, F., Renauld, M., Standaert, F.-X., van Oldeneel tot Oldenzeel, L., Veyrat-Charvillon, N.: Efficient removal of random delays from embedded software implementations using hidden markov models. In: Mangard, S. (ed.) CARDIS 2012. LNCS, vol. 7771, pp. 123–140. Springer, Heidelberg (2013)
Coron, J.-S., Kizhvatov, I.: Analysis and improvement of the random delay countermeasure of CHES 2009. In: Mangard, S., Standaert, F.-X. (eds.) CHES 2010. LNCS, vol. 6225, pp. 95–109. Springer, Heidelberg (2010)
Mather, L., Oswald, E., Bandenburg, J., Wójcik, M.: Does my device leak information? An a priori statistical power analysis of leakage detection tests. In: Sako, K., Sarkar, P. (eds.) ASIACRYPT 2013, Part I. LNCS, vol. 8269, pp. 486–505. Springer, Heidelberg (2013)
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)
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)
Kocher, P.C.: 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)
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)
European Network of Excellence (ECRYPT). The side channel cryptanalysis lounge. http://www.crypto.ruhr-uni-bochum.de/ensclounge.html
Standaert, F.-X., Koeune, F., Schindler, W.: How to compare profiled side-channel attacks? In: Abdalla, M., Pointcheval, D., Fouque, P.-A., Vergnaud, D. (eds.) ACNS 2009. LNCS, vol. 5536, pp. 485–498. Springer, Heidelberg (2009)
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)
Pearson, K.: On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. Philos. Mag. Ser. 5 50(302), 157–175 (1900)
Acknowledgments
This work was supported by the National Basic Research Program of China (No. 2013CB338003), the National Natural Science Foundation of China (Nos. 61472416, 61272478), and the National Key Scientific and Technological Project (No. 2014ZX01032401-001).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Appendix A: The Proof of Lemma 2
Appendix A: The Proof of Lemma 2
Proof:
For simplicity, we only consider the case when \(N=2\). For the case \(N>2\), this Lemma holds similarly.
Let \((\xi ,\eta )\) denote a 2 dimensional random vector. The continuous distribution function and the probability density function of the 2 dimensional random vector respectively are F(x, y) and p(x, y). Then, the marginal distribution functions are as follows:
The marginal density functions are as follows:
For 2 dimensional multivariate Gaussian distribution, it has that
where
and the values \(a,b,\sigma _1,\sigma _2,r\) are constant, \(\sigma _1>0,\sigma _2>0,|r|<1\). The probability density function p(x, y) can be rewritten as follows
Let
and it has that
Therefore, \(p_1(x)\) is the probability density function of the normal distribution \(\mathcal {N}(a,\sigma ^2_1)\). Similarly, we can prove that
In this way, Lemma 2 is proven. \(\square \)
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Fan, G., Zhou, Y., Zhang, H., Feng, D. (2015). How to Choose Interesting Points for Template Attacks More Effectively?. In: Yung, M., Zhu, L., Yang, Y. (eds) Trusted Systems. INTRUST 2014. Lecture Notes in Computer Science(), vol 9473. Springer, Cham. https://doi.org/10.1007/978-3-319-27998-5_11
Download citation
DOI: https://doi.org/10.1007/978-3-319-27998-5_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-27997-8
Online ISBN: 978-3-319-27998-5
eBook Packages: Computer ScienceComputer Science (R0)