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 …

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 …

Profiled side-channel attacks represent a practical threat to digital devices, thereby having
the potential to disrupt the foundation of e-commerce, the Internet of Things (IoT), and smart …

We take advantage of a recently published open source implementation of the AES
protected with a mix of countermeasures against side-channel attacks to discuss both the …

We consider the question whether synchronization/alignment methods are still
useful/necessary in the context of side-channel attacks exploiting deep learning algorithms …

Deep learning (DL) has proven to be very effective for image recognition tasks, with a large
body of research on various model architectures for object classification. Straight-forward …

Side-Channel Attacks (SCAs) are a powerful method to attack implementations of
cryptographic algorithms. State-of-the-art techniques such as template attacks and …