Wednesday
Room 4
10:20 - 11:20
(UTC+01)
Talk (60 min)
Navigating the Security and Privacy Landscape of Modern AI
In this session, we will overview the general security and privacy landscape of AI technologies, including foundational machine learning, deep learning, and large language models.
The fast-evolving ecosystem of AI-enabled applications has exposed a complex interplay of vulnerabilities, some stemming from intrinsic pitfalls of data-driven AI and others arising from its unsafe integration into real-world applications. The goal of the session is to raise awareness about the underlying principles and practical challenges of AI security and privacy, and the ongoing mitigation efforts by both academic and industry players.
Vera Rimmer
Dr. Vera Rimmer is a research expert at the DistriNet research group at KU Leuven, where she conducts and leads research activities in the intersection of security, privacy and AI. She completed her PhD at KU Leuven in 2022, with the main focus on applying deep learning in anonymity networks and network defense systems. Currently, Vera and her team explore data analytics in network intrusion and malware detection, and trustworthiness of data-driven AI in the wider ICT context. Vera is interested in developing comprehensive understanding, reasonable expectations and mitigation of risks of data-driven AI in the age of uncontrolled data collection and inference.