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2016 | OriginalPaper | Buchkapitel

Towards Easy Leakage Certification

verfasst von : François Durvaux, François-Xavier Standaert, Santos Merino Del Pozo

Erschienen in: Cryptographic Hardware and Embedded Systems – CHES 2016

Verlag: Springer Berlin Heidelberg

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Abstract

Side-channel attacks generally rely on the availability of good leakage models to extract sensitive information from cryptographic implementations. The recently introduced leakage certification tests aim to guarantee that this condition is fulfilled based on sound statistical arguments. They are important ingredients in the evaluation of leaking devices since they allow a good separation between engineering challenges (how to produce clean measurements) and cryptographic ones (how to exploit these measurements). In this paper, we propose an alternative leakage certification test that is significantly simpler to implement than the previous proposal from Eurocrypt 2014. This gain admittedly comes at the cost of a couple of heuristic (yet reasonable) assumptions on the leakage distribution. To confirm its relevance, we first show that it allows confirming previous results of leakage certification. We then put forward that it leads to additional and useful intuitions regarding the information losses caused by incorrect assumptions in leakage modeling.

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Fußnoten
2
Note that theoretical approches to guarantee that a distribution is well characterized by its moments (such as Carleman’s condition [22]) typically apply when considering an infinite number of them and in general, no distribution is determined by a finite number of moments. So the restriction of our reasoning to specific classes of meaningful distributions is in fact necessary for our approach to be sound. Besides, note also that non-parametric PDF estimations may not suffer from assumption errors (at the cost of a significantly increased estimation cost), so are out of scope here.
 
3
Student’s t distribution is a parametric probability density function whose only parameter is its number of freedom degrees, that can be directly derived from k and the previous \(\sigma \) estimates as: \(d_f = (k-1)\times [(\hat{\sigma }_y^d)^2+(\tilde{\sigma }_y^d)^2]^2/[(\hat{\sigma }_y^d)^4+(\tilde{\sigma }_y^d)^4]\).
 
4
This happens for the selected time sample because of pipelining effects in the AVR microcontroller. Note that as in [8], the linear model did not exhibit any assumption error for other time samples given the amount of measured traces.
 
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Metadaten
Titel
Towards Easy Leakage Certification
verfasst von
François Durvaux
François-Xavier Standaert
Santos Merino Del Pozo
Copyright-Jahr
2016
Verlag
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-662-53140-2_3