Paper 2013/849

Pushing the Limit of Non-Profiling DPA using Multivariate Leakage Model

Suvadeep Hajra and Debdeep Mukhopadhyay

Abstract

Profiling power attacks like Template attack and Stochastic attack optimize their performance by jointly evaluating the leakages of multiple sample points. However, such multivariate approaches are rare among non-profiling Differential Power Analysis (DPA) attacks, since integration of the leakage of a higher SNR sample point with the leakage of lower SNR sample point might result in a decrease in the overall performance. One of the few successful multivariate approaches is the application of Principal Component Analysis (PCA) for non-profiling DPA. However, PCA also performs sub-optimally in the presence of high noise. In this paper, a multivariate model for an FPGA platform is introduced for improving the performances of non-profiling DPA attacks. The introduction of the proposed model greatly increases the success rate of DPA attacks in the presence of high noise. The experimental results on both simulated power traces and real power traces are also provided as an evidence.

Metadata
Available format(s)
PDF
Category
Implementation
Publication info
Published elsewhere. Minor revision. INSCRYPT 2013
Keywords
Differential Power Attack (DPA)Correlation Power Attack (CPA)leakage modelmultivariate leakage modelnon-profiling attackmultivariate distinguishermultivariate DPA.
Contact author(s)
suvadeep hajra @ gmail com
History
2013-12-17: received
Short URL
https://ia.cr/2013/849
License
Creative Commons Attribution
CC BY

BibTeX

@misc{cryptoeprint:2013/849,
      author = {Suvadeep Hajra and Debdeep Mukhopadhyay},
      title = {Pushing the Limit of Non-Profiling DPA using Multivariate Leakage Model},
      howpublished = {Cryptology ePrint Archive, Paper 2013/849},
      year = {2013},
      note = {\url{https://eprint.iacr.org/2013/849}},
      url = {https://eprint.iacr.org/2013/849}
}
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