Side-channel analysis has changed the field of cryptography and security and it became the most common cause of real-world security applications failing today. In this talk we give an overview of side-channel attacks on implementations of cryptography and countermeasures. We discuss the ways Machine learning and AI changed the side-channel analysis landscape and attackers’ capabilities in particular. We survey several examples of AI assisting with leakage assessment and discuss the impact of AI on the field and security evaluations in particular. We also describe the way side-channel analysis threatens AI implementations e.g. neural nets architectures that are commonly used in practice. In the end, we identify some avenues for future research.
Short Bio:
Lejla Batina is a professor in embedded systems security at Radboud University in Nijmegen, the Netherlands. She received her Ph.D. from KU Leuven, Belgium (2005) and before that she worked as a cryptographer for SafeNet B.V. in The Netherlands (2001–2003).
She has coauthored close to 160 refereed articles on various topics in applied cryptography and embedded systems security. Her current research interests include physical attacks on cryptographic implementations and the impact of AI on hardware security.
She is a senior member of IEEE and an Editorial board member of top journals in security, such as IEEE Transactions on Information Forensics and Security and ACM Transactions on Embedded Computing Systems. She was program co-chair of CHES 2014, ACM WiSec 2021, Africacrypt 2022, SPACE 2020-2022, ACNS2024 and she co-organized (as general chair) IACR flagship conferences such as EUROCRYPT (2020-2021) and Real-world crypto symposium (RWC) 2022. Her research group at Radboud consists of 15 researchers and 12 Ph.D. students have so far graduated under her supervision.
Date/Time:
Thursday, 12th of October, at 10 am.
Location:
The talk will take place in a hybrid mode with a physical presence in the Bernd Therre lecture hall at CISPA and via Zoom:
https://cispa-de.zoom-x.de/j/62027159245?pwd=djgrdkpEZjZCYXhBSTVFZTE4dVNzdz09
ID: 620 2715 9245
Passcode: j14L8*