Paper 2021/904

Spatial Dependency Analysis to Extract Information from Side-Channel Mixtures

Aurélien Vasselle, Hugues Thiebeauld, and Philippe Maurine


Practical side-channel attacks on recent devices may be challenging due to the poor quality of acquired signals. It can originate from different factors, such as the growing architecture complexity, especially in System-on-Chips, creating unpredictable and concurrent operation of multiple signal sources on the device. This work makes use of mixture distributions to formalize this complexity, allowing us to explain the benefit of using a technique like Scatter, where different samples of the traces are aggregated into the same distribution. Some observations of the conditional mixture distributions are made in order to model the leakage in such context. From this, we infer local coherency of information held in the distribution as a general property of side-channel leakage in mixture distributions. This leads us to introduce how spatial analysis tools, such as Moran's Index, can be used to significantly improve non-profiled attacks compared to other techniques from the state-of-the-art. Exploitation of this technique is experimentally shown very promising, as demonstrated on two AES implementations including masking and shuffling countermeasures.

Available format(s)
Publication info
Preprint. MINOR revision.
Side-channel AnalysisSystem-on-ChipsMixture distributionInteraction InformationSpatial AnalysisMoran's IndexASCAD
Contact author(s)
aurelien vasselle @ eshard com
2021-07-05: received
Short URL
Creative Commons Attribution


      author = {Aurélien Vasselle and Hugues Thiebeauld and Philippe Maurine},
      title = {Spatial Dependency Analysis to Extract Information from Side-Channel Mixtures},
      howpublished = {Cryptology ePrint Archive, Paper 2021/904},
      year = {2021},
      note = {\url{}},
      url = {}
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