Vera Rimmer
Research Expert at DistriNet, KU Leuven, Belgium
I conduct and lead research activities at the intersection of security, privacy, and AI at DistriNet. Our team explores data analytics in network intrusion and malware detection, privacy-enhancing technologies, and trustworthiness of data-driven AI in the wider ICT context. The driving force behind my work is examining the optimal role of technology in our society, particularly AI, while balancing its benefits and challenges. In this age of massive surveillance and uncontrolled data collection and inference, I am committed to forming a comprehensive understanding, reasonable expectations, and effective strategies to mitigate the risks of applied AI.
Beyond academic research, our team is committed to sharing scientific knowledge through direct collaboration with industry. We work with companies seeking practical guidance on how to safely and securely leverage modern AI technologies, such as deep learning, foundation models, and integration of large language models.
What's new?
| Oct 04, 2025 | We opened the IEEE EuroS&P 2026 Call for Workshops! Workshop proposals are due on October 24 AoE. Co-chaired with Christian Wressnegger. |
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| Sep 12, 2025 | Concluded an amazing, 4th edition of our Summer School on Security & Privacy in the age of AI in KU Leuven. Check out the program and stay tuned by joining the mailing list. |
| Aug 15, 2025 | I was recognized as an USENIX Security 2025 Notable Reviewer. |
| Jul 10, 2025 | Our paper “The Adaptive Arms Race: Redefining Robustness in AI Security”—on a reinforcement learning approach for evaluating adversarial AI attacks and defenses—has been accepted to RAID. |
| Jun 26, 2025 | I will co-organize the poster session at USENIX Security 2025, submissions due on July 14. Co-chaired with Sarah Scheffler. |
Selected publications
- WoRMAPosition Paper: On Advancing Adversarial Malware Generation Using Dynamic FeaturesIn Proceedings of the 1st Workshop on Robust Malware Analysis, 2022
- SpringerOpen-World Network Intrusion DetectionIn Security and Artificial Intelligence: A Crossdisciplinary Approach, 2022
- WTMCTroubleshooting an intrusion detection dataset: the CICIDS2017 case studyIn 2021 IEEE Security and Privacy Workshops (SPW), 2021
- WOOTFishy faces: Crafting adversarial images to poison face authenticationIn 12th USENIX Workshop on Offensive Technologies (WOOT 18), 2018
We opened the
I was recognized as an
Our paper “The Adaptive Arms Race: Redefining Robustness in AI Security”—on a reinforcement learning approach for evaluating adversarial AI attacks and defenses—has been accepted to