Vera Rimmer

Research Expert at DistriNet, KU Leuven, Belgium

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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 Image We opened the IEEE EuroS&P 2026 Call for Workshops! Workshop proposals are due on October 24 AoE. Co-chaired with Christian Wressnegger.
Sep 12, 2025 Image 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 Image I was recognized as an USENIX Security 2025 Notable Reviewer.
Jul 10, 2025 Image 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 Image I will co-organize the poster session at USENIX Security 2025, submissions due on July 14. Co-chaired with Sarah Scheffler.

Selected publications

  1. RAID
    The Adaptive Arms Race: Redefining Robustness in AI Security
    Ilias Tsingenopoulos, Vera Rimmer, Davy Preuveneers, Fabio Pierazzi, Lorenzo Cavallaro, and Wouter Joosen
    In , 2025
  2. arXiv
    FlowPure: Continuous Normalizing Flows for Adversarial Purification
    Elias Collaert, Abel Rodrı́guez, Sander Joos, Lieven Desmet, and Vera Rimmer
    arXiv preprint arXiv:2505.13280, 2025
  3. SatML
    SoK: On the offensive potential of AI
    Saskia Laura Schröer, Giovanni Apruzzese, Soheil Human, Pavel Laskov, Hyrum S Anderson, Edward WN Bernroider, and 10 more authors
    In 3rd IEEE Conference on Secure and Trustworthy Machine Learning, 2025
  4. PETS
    Trace Oddity: Methodologies for Data-Driven Traffic Analysis on Tor
    Vera Rimmer, Theodor Schnitzler, Tom Van Goethem, Abel Rodrı́guez Romero, Wouter Joosen, and Katharina Kohls
    Proceedings on Privacy Enhancing Technologies, 2022
  5. WoRMA
    Position Paper: On Advancing Adversarial Malware Generation Using Dynamic Features
    Ali Shafiei, Vera Rimmer, Ilias Tsingenopoulos, Lieven Desmet, and Wouter Joosen
    In Proceedings of the 1st Workshop on Robust Malware Analysis, 2022
  6. Springer
    Open-World Network Intrusion Detection
    Vera Rimmer, Azqa Nadeem, Sicco Verwer, Davy Preuveneers, and Wouter Joosen
    In Security and Artificial Intelligence: A Crossdisciplinary Approach, 2022
  7. WTMC
    Troubleshooting an intrusion detection dataset: the CICIDS2017 case study
    Gints Engelen, Vera Rimmer, and Wouter Joosen
    In 2021 IEEE Security and Privacy Workshops (SPW), 2021
  8. NDSS
    Automated Website Fingerprinting through Deep Learning
    Vera Rimmer, Davy Preuveneers, Marc Juarez, Tom Van
Goethem, and Wouter Joosen
    In Proceedings of the 25nd Network and Distributed System
Security Symposium (NDSS 2018), 2018
  9. WOOT
    Fishy faces: Crafting adversarial images to poison face authentication
    In 12th USENIX Workshop on Offensive Technologies (WOOT 18), 2018