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Wu, L. (author), Perin, G. (author), Picek, S. (author)
Deep learning-based side-channel analysis is rapidly positioning itself as a de-facto standard for the most powerful profiling side-channel analysis.The results from the last few years show that deep learning techniques can efficiently break targets that are even protected with countermeasures. While there are constant improvements in making...
conference paper 2022
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Rijsdijk, J. (author), Wu, L. (author), Perin, G. (author), Picek, S. (author)
Deep learning represents a powerful set of techniques for profiling side-channel analysis. The results in the last few years show that neural network architectures like multilayer perceptron and convolutional neural networks give strong attack performance where it is possible to break targets protected with various coun-termeasures....
journal article 2021
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Perin, G. (author), Chmielewski, Łukasz (author), Batina, Lejla (author), Picek, S. (author)
To mitigate side-channel attacks, real-world implementations of public-key cryptosystems adopt state-of-the-art countermeasures based on randomization of the private or ephemeral keys. Usually, for each private key operation, a “scalar blinding” is performed using 32 or 64 randomly generated bits. Nevertheless, horizontal attacks based on a...
journal article 2020