On the Relationship between Correlation Power Analysis and the Stochastic Approach: An ASIC Designer Perspective | SpringerLink
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On the Relationship between Correlation Power Analysis and the Stochastic Approach: An ASIC Designer Perspective

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Progress in Cryptology – INDOCRYPT 2013 (INDOCRYPT 2013)

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Abstract

The design and the security verification of side-channel resistant cryptographic hardware often represent an iterative process. This process essentially consists of a detection phase (\(\mathcal{DP}\)), where the information leakage is identified and a correction phase (\(\mathcal{CP}\)), where design flaws are corrected. Correlation Power Analysis (CPA) and the Stochastic Approach (SA) are two candidate tools to perform the \(\mathcal{DP}\) and to support designers in the \(\mathcal{CP}\). However, until now, the relationship between these two tools has not been discussed yet and it is uncertain from a designer point of view, what informative feedback can be gained from these methods, especially when it comes to evaluate high-dimensional leakage models. In this work, we investigate the relationship between CPA and the SA from both a mathematical and empirical point of view. In particular, we demonstrate that the informative feedback provided by the SA is transferable to a linear combination of CPA attacks and discuss the implications of this entanglement, when it comes to pinpoint the high-dimensional leakage of simulated leakage data and simulated power traces of an ASIC implementation of Present.

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De Santis, F., Kasper, M., Mangard, S., Sigl, G., Stein, O., Stöttinger, M. (2013). On the Relationship between Correlation Power Analysis and the Stochastic Approach: An ASIC Designer Perspective. In: Paul, G., Vaudenay, S. (eds) Progress in Cryptology – INDOCRYPT 2013. INDOCRYPT 2013. Lecture Notes in Computer Science, vol 8250. Springer, Cham. https://doi.org/10.1007/978-3-319-03515-4_14

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  • DOI: https://doi.org/10.1007/978-3-319-03515-4_14

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03514-7

  • Online ISBN: 978-3-319-03515-4

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