Improving machine learning based side-channel analysis: can dropout be dropped out?

Analysing physical leakages (e.g. power consumption and electromagnetic radiation) of cryptographic devices can be used by adversaries to extract secret keys. Over the last couple of years, researchers have shown that machine learning has potential for this process. Machine learning models need to be fine-tuned to enhance key extraction...

BagDrop: Computationally Feasible Approximate Bagging with Neural Networks

Overfitting is a common problem when learning models from noisy observational data. This problem is especially present in very flexible models, such as Neural Networks, which can easily fit to spurious patterns in the data that are not indicative of true underlying patterns. One technique that conquers the problem of overfitting is Bagging, an...