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Title:
A New Second Order Side Channel Attack Based on Linear Regression
Authors: Julien Doget, Guillaume Dabosville, Emmanuel Prouff
Abstract:Embedded implementations of cryptographic primitives need protection against Side Channel Analysis. Stochastic attacks, introduced by Schindler et al. at CHES 2005, are an example of such an analysis. They offer a pertinent alternative to template attacks which efficiency is optimal, and they can theoretically defeat any kind of countermeasure including masking. In both template and stochastic attacks, the adversary needs to be able to carry out a profiling stage on a perfect copy of the target device. This makes them interesting tools to study the resistance of implementations against such a powerful adversary, but it limits their pertinency in practice. It is indeed difficult to have an open access to a copy of the device under attack and, even when it is possible, it remains difficult to exploit templates acquired on one device to attack another one. In this paper, we propose a new attack technique which shares many similarities with stochastic attacks but does not require any profiling stage. As a consequence, no copy of the device is needed anymore. We conduct an in-depth analysis of this new attack to highlight its core foundations. Then, we apply it to widely used masking schemes and we illustrate its interest by a series of experiments on simulated and real curves.
ePrint: https://eprint.iacr.org/2011/505
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