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Spatial dependency analysis to extract information from side-channel mixtures: extended version

Spatial dependency analysis to extract information from side-channel mixtures: extended version 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 in 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 expression of the 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 by its application on two AES implementations including masking and shuffling countermeasures. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Cryptographic Engineering Springer Journals

Spatial dependency analysis to extract information from side-channel mixtures: extended version

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References (9)

Publisher
Springer Journals
Copyright
Copyright © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
ISSN
2190-8508
eISSN
2190-8516
DOI
10.1007/s13389-022-00307-9
Publisher site
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Abstract

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 in 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 expression of the 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 by its application on two AES implementations including masking and shuffling countermeasures.

Journal

Journal of Cryptographic Engineering – Springer Journals

Published: Nov 1, 2023

Keywords: Side-channel analysis; System-on-chips; Mixture distribution; Interaction information; Spatial analysis; Moran’s index; ASCAD

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