Vera Rimmer

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?

Apr 16, 2026	Our paper with INESC TEC “It Works on My Machine: A SoK on Reproducibility and Replicability in ML-Based Ransomware Detection” has been accepted to WoRMA 2026, co-located with IEEE EuroS&P 2026.
Apr 15, 2026	Applications to the 5th edition of our Summer School on Security & Privacy in the age of AI in KU Leuven are open!.
Mar 25, 2026	I was recognized as a IEEE SaTML 2026 Distinguished Reviewer.
Mar 10, 2026	I will give a keynote talk at DeMeSSAI co-located with IEEE EuroS&P in Lisbon, Portugal.
Nov 10, 2025	Our 5th Workshop on Rethinking Malware Analysis (WoRMA) is accepted to appear at IEEE EuroS&P 2026 in Lisbon, Portugal! Co-chaired with Luca Demetrio and Daniel Arp.

Selected publications

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

arXiv Bib PDF

@inproceedings{tsingenopoulos2025adaptive,
  title = {The Adaptive Arms Race: Redefining Robustness in AI Security},
  author = {Tsingenopoulos, Ilias and Rimmer, Vera and Preuveneers, Davy and Pierazzi, Fabio and Cavallaro, Lorenzo and Joosen, Wouter},
  year = {2025},
  organization = {Research in Attacks, Intrusions and Defenses (RAID)},
}

WAITI

On the Potential of LLMs for Offensive Security: Benchmarks vs. Operational Reality

Ruben Missotten, Vera Rimmer, Wim Mees, and Lieven Desmet

In 2025 Annual Computer Security Applications Conference Workshops (ACSAC Workshops), 2025

Bib PDF

@inproceedings{missotten2025potential,
  title = {On the Potential of LLMs for Offensive Security: Benchmarks vs. Operational Reality},
  author = {Missotten, Ruben and Rimmer, Vera and Mees, Wim and Desmet, Lieven},
  booktitle = {2025 Annual Computer Security Applications Conference Workshops (ACSAC Workshops)},
  pages = {420--427},
  year = {2025},
  organization = {IEEE},
}

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

arXiv Bib

@article{collaert2025flowpure,
  title = {FlowPure: Continuous Normalizing Flows for Adversarial Purification},
  author = {Collaert, Elias and Rodr{\'\i}guez, Abel and Joos, Sander and Desmet, Lieven and Rimmer, Vera},
  journal = {arXiv preprint arXiv:2505.13280},
  year = {2025},
}

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

arXiv Bib

@inproceedings{schroer2025sok,
  title = {SoK: On the offensive potential of AI},
  author = {Schröer, Saskia Laura and Apruzzese, Giovanni and Human, Soheil and Laskov, Pavel and Anderson, Hyrum S and Bernroider, Edward WN and Fass, Aurore and Nassi, Ben and Rimmer, Vera and Roli, Fabio and Salam, Samer and Shen, Ashley and Sunyaev, Ali and Wadwha-Brown, Tim and Wagner, Isabel and Wang, Gang},
  booktitle = {3rd IEEE Conference on Secure and Trustworthy Machine Learning},
  year = {2025},
}

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

Bib Website

@article{rimmer2022trace,
  title = {Trace Oddity: Methodologies for Data-Driven Traffic Analysis on Tor},
  author = {Rimmer, Vera and Schnitzler, Theodor and Van Goethem, Tom and Romero, Abel Rodr{\'\i}guez and Joosen, Wouter and Kohls, Katharina},
  journal = {Proceedings on Privacy Enhancing Technologies},
  volume = {3},
  pages = {314--335},
  year = {2022},
}

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

Bib

@inproceedings{shafiei2022position,
  title = {Position Paper: On Advancing Adversarial Malware Generation Using Dynamic Features},
  author = {Shafiei, Ali and Rimmer, Vera and Tsingenopoulos, Ilias and Desmet, Lieven and Joosen, Wouter},
  booktitle = {Proceedings of the 1st Workshop on Robust Malware Analysis},
  pages = {15--20},
  year = {2022},
}

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

Bib

@incollection{rimmer2022open,
  title = {Open-World Network Intrusion Detection},
  author = {Rimmer, Vera and Nadeem, Azqa and Verwer, Sicco and Preuveneers, Davy and Joosen, Wouter},
  booktitle = {Security and Artificial Intelligence: A Crossdisciplinary Approach},
  pages = {254--283},
  year = {2022},
  publisher = {Springer},
}

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

Bib

@inproceedings{engelen2021troubleshooting,
  title = {Troubleshooting an intrusion detection dataset: the CICIDS2017 case study},
  author = {Engelen, Gints and Rimmer, Vera and Joosen, Wouter},
  booktitle = {2021 IEEE Security and Privacy Workshops (SPW)},
  pages = {7--12},
  year = {2021},
  organization = {IEEE},
}

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

Bib Website

@inproceedings{rimmer2018automated,
  title = {Automated Website Fingerprinting through Deep Learning},
  author = {Rimmer, Vera and Preuveneers, Davy and Juarez, Marc and Van Goethem, Tom and Joosen, Wouter},
  booktitle = {Proceedings of the 25nd Network and Distributed System Security Symposium (NDSS 2018)},
  year = {2018},
  organization = {Internet Society},
}

WOOT

Fishy faces: Crafting adversarial images to poison face authentication

In 12th USENIX Workshop on Offensive Technologies (WOOT 18), 2018

Bib

@inproceedings{garofalo2018fishy,
  title = {Fishy faces: Crafting adversarial images to poison face authentication},
  author = {},
  booktitle = {12th USENIX Workshop on Offensive Technologies (WOOT 18)},
  year = {2018},
}