Stjepan Picek

Talk Title

Challenges in Deep Learning-based Profiled Side-channel Analysis

Abstract

Recent years showed that machine learning can be a powerful paradigm for implementation attacks, especially profiling side-channel attacks (SCAs). Still, despite all the success, we are limited in our understanding when and how to select appropriate machine learning techniques. Additionally, the results we can obtain are empirical and valid for specific cases where generalization is often difficult. In this talk, we discuss several well-known machine learning techniques, the results obtained, and their limitations. Next, we concentrate on deep learning techniques and potential benefits such techniques can bring to SCA, with an emphasis on real-world scenarios.

Short Bio

Stjepan Picek is an assistant professor in the Cybersecurity group at TU Delft, The Netherlands. His research interests are security/cryptography, machine learning, and evolutionary computation. Prior to the assistant professor position, Stjepan was a postdoctoral researcher at MIT, USA and KU Leuven, Belgium. Stjepan finished his PhD in 2015 with a topic on cryptology and evolutionary computation.

Stjepan has several years of experience working in industry and government. Up to now, he gave more than 15 invited talks at conferences and summer schools and published more than 80 refereed papers. Stjepan is a member of the organization committee for International Summer School in Cryptography, president of the Croatian IEEE CIS Chapter and general co-chair for Eurocrypt 2020.