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Heuser, Annelie (author), Picek, S. (author), Guilley, Sylvain (author), Mentens, Nele (author)Side-channel attacks represent a powerful category of attacks against cryptographic devices. Still, side-channel analysis for lightweight ciphers is much less investigated than for instance for AES. Although intuition may lead to the conclusion that lightweight ciphers are weaker in terms of side-channel resistance, that remains to be...journal article 2020
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Kim, Jaehun (author), Picek, S. (author), Heuser, Annelie (author), Bhasin, Shivam (author), Hanjalic, A. (author)Profiled side-channel analysis based on deep learning, and more precisely Convolutional Neural Networks, is a paradigm showing significant potential. The results, although scarce for now, suggest that such techniques are even able to break cryptographic implementations protected with countermeasures. In this paper, we start by proposing a new...journal article 2019
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Picek, S. (author), Heuser, Annelie (author), Jovic, Alan (author), Batina, Lejla (author)Profiled side-channel attacks consist of several steps one needs to take. An important, but sometimes ignored, step is a selection of the points of interest (features) within side-channel measurement traces. A large majority of the related works start the analyses with an assumption that the features are preselected. Contrary to this...journal article 2019
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Picek, S. (author), Heuser, Annelie (author), Jovic, Alan (author), Bhasin, Shivam (author), Regazzoni, Francesco (author)We concentrate on machine learning techniques used for profiled side-channel analysis in the presence of imbalanced data. Such scenarios are realistic and often occurring, for instance in the Hamming weight or Hamming distance leakage models. In order to deal with the imbalanced data, we use various balancing techniques and we show that most of...journal article 2018
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