AI has provided us with the ability to automate tasks, extract information from vast amounts of
data, and synthesize media that is nearly indistinguishable from the real thing. However …

Profiled side-channel analysis based on deep learning, and more precisely Convolutional
Neural Networks, is a paradigm showing significant potential. The results, although scarce …

We concentrate on machine learning techniques used for profiled sidechannel analysis in
the presence of imbalanced data. Such scenarios are realistic and often occurring, for …

This paper has four main contributions. First, we calculate the predicted difference
distribution of Speck32/64 with one specific input difference under the Markov assumption …

As side‐channel analysis and machine learning algorithms share the same objective of
classifying data, numerous studies have been proposed for adapting machine learning to …

In the profiled side-channel analysis, deep learning-based techniques proved to be very
successful even when attacking targets protected with countermeasures. Still, there is no …

Today's mobile devices contain densely packaged system-on-chips (SoCs) with multi-core,
high-frequency CPUs and complex pipelines. In parallel, sophisticated SoC-assisted …

When machining difficult-to-cut materials, a massive heat will generate and then cause
serious thermal damages to both workpiece and cutting tools. Oscillating heat pipes have …

The usage of deep learning in profiled side-channel analysis requires a careful selection of
neural network hyperparameters. In recent publications, different network architectures have …

We present the first deep learning-based side-channel attack on AES-128 using far field
electromagnetic emissions as a side channel. Our neural networks are trained on traces …