Efficient Stochastic Methods: Profiled Attacks Beyond 8 Bits

  • Marios O. Choudary
  • Markus G. Kuhn
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8968)


Template attacks and stochastic models are among the most powerful side-channel attacks. However, they can be computationally expensive when processing a large number of samples. Various compression techniques have been used very successfully to reduce the data dimensionality prior to applying template attacks, most notably Principal Component Analysis (PCA) and Fisher’s Linear Discriminant Analysis (LDA). These make the attacks more efficient computationally and help the profiling phase to converge faster. We show how these ideas can also be applied to implement stochastic models more efficiently, and we also show that they can be applied and evaluated even for more than eight unknown data bits at once.


Side-channel attacks Template attack Stochastic model PCA LDA 



The first author is a recipient of the Google Europe Fellowship in Mobile Security, and this research was supported in part by this fellowship. The opinions expressed in this paper do not represent the views of Google unless otherwise explicitly stated.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Computer LaboratoryUniversity of CambridgeCambridgeUK

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