Side-Channel Attacks using Convolutional Neural Networks: A Study on the performance of Convolutional Neural Networks on side-channel data

Side-Channel Attacks, are a prominent type of attacks, used to break cryptographic implementations on a computing system. They are based on information "leaked" by the hardware of a computing system, rather than the encryption algorithm itself. Recent studies showed that Side-Channel Attacks can be performed using Deep Learning models. In this...

Towards Understanding of Deep Learning in Profiled Side-Channel Analysis: Similarity of predictors measured and explained

Side-channel attacks (SCA) aim to extract a secret cryptographic key from a device, based on unintended leakage. Profiled attacks are the most powerful SCAs, as they assume the attacker has a perfect copy of the target device under his control. In recent years, machine learning (ML) and deep learning (DL) techniques have became popular as...

Interpreting Information of Deep Neural Networks for Profiled Side Channel Analysis

Security has become ever more important in today's quickly growing digital world as the number of digital assets has quickly grown. Our thesis focuses on devices that compute a secure cryptographic operation such that information can be communicated or authenticated. The attack vector utilized is known as Profiled Side-Channel Analysis (SCA)...