The Circle of DL-SCA: Improving Deep Learning-based Side-channel Analysis

For almost three decades, side-channel analysis has represented a realistic and severe threat to embedded devices' security. As a well-known and influential class of implementation attacks, side-channel analysis has been applied against cryptographic implementations, processors, communication systems, and, more recently, machine learning models....

Autoencoder-enabled model portability for reducing hyperparameter tuning efforts in side-channel analysis

Hyperparameter tuning represents one of the main challenges in deep learning-based profiling side-channel analysis. For each different side-channel dataset, the typical procedure to find a profiling model is applying hyperparameter tuning from scratch. The main reason is that side-channel measurements from various targets contain different...

Reinforcement learning for hyperparameter tuning in deep learning-based side-channel analysis

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....