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Email: first.last at kuleuven.beAbout Me
Hey there! I'm Vera and I work as a post-doctoral researcher at the DistriNet lab in KU Leuven, Belgium, where I have recently completed my PhD in computer science under the supervision of Prof. Wouter Joosen and Dr. Davy Preuveneers. I study cybersecurity and privacy-enhancing technologies; data analytics in cybersecurity and privacy; applied machine learning and deep learning; privacy and trustworthiness of applied data-driven AI. My published research revolves around studying deep learning as a threat against anonymous communication, and various aspects of AI-enabled network intrusion detection and authentication. I am also closely involved in teaching and supervising activities at KU Leuven and in academic service for the security & privacy community.
Apart from research, my experience also includes three years of working in industry, where I did software engineering, applied cryptography and penetration testing. More information can be found in my CV (last update in August 2023).
I am generally interested in developing comprehensive understanding, reasonable expectations and mitigation of risks of data-driven AI in the ICT context. The driving force behind my work is exploring the optimal role of AI in our society, in the age of uncontrolled data collection and inference, while balancing its benefits and potential harm.
Recent News
- March 2024 I had the pleasure to give a lecture on "Vulnerabilities of Large Language Models" at the University of Edinburgh.
- March 2024 Looking forward to returning to SecAppDev in June after 7 years, this time to contribute a talk for practitioners on the implications of Large Language Models on application security! And in June, together with Lieven Desmet, we will give a lecture on the interplay of AI and security to PhD students for the COSIC course.
- March 2024 I will attend IEEE S&P, DLSP and SAGAI in May 2024 in San Francisco, US.
- February 2024 Save the date! On September 10-13, together with Wouter Joosen, Fabio Roli and Lorenzo Cavallaro, I will co-organize the 3rd Edition of Summer School on Security & Privacy in the age of AI. Applications open on June 1.
- November 2023 Together with Fabio Pierazzi and Savino Dambra, I will co-organize the 3rd Workshop on Rethinking Malware Analysis (WoRMA), co-located with IEEE EuroS&P 2024 in Vienna!
- November 2023 I gave an invited talk in Chalmers on the topic of "The ambivalent role of deep learning in traffic analysis attacks and defenses".
- October 2023 I took part in the Dagstuhl seminar on AI-powered network attacks and defense as a team leader on AI-enabled defenses -- reports will be available soon.
- September 2023 We hosted the 2nd edition of our successful PhD Summer School on Security & Privacy in the Age of AI here at DistriNet, KU Leuven, where I gave a lecture titled "Applied deep learning in security and privacy research".
- August 2023 I took part in the prestigious Machine Learning school in Thessaloniki (M2L 2023) organized by DeepMind!
- July 2023 Together with Azqa Nadeem, I co-organized mentoring sessions at IEEE Euro S&P in Delft, NL.
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December 2022 Defended my PhD!
Read the manuscript here, watch the defense here.
Selected Publications
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Ilias Tsingenopoulos, Vera Rimmer, Davy Preuveneers, Fabio Pierazzi, Lorenzo Cavallaro, Wouter Joosen
On Adaptive Decision-Based Attacks and Defenses (Extended Abstract), Deep Learning Security and Privacy Workshop (DLSP), 2024. -
Vera Rimmer, Theodor Schnitzler, Tom Van Goethem, Abel Rodríguez Romero, Wouter Joosen, Katharina Kohls
Trace Oddity: Methodologies for Data-Driven Traffic Analysis on Tor, Proceedings on Privacy Enhancing Technologies (PoPETS), 2022.
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Ali Shafiei, Vera Rimmer, Ilias Tsingenopolous, Lieven Desmet, Wouter Joosen
Positiong Paper: on Advancing Adversarial Malware Generation using Dynamic Features, Proceedings of the 1st Workshop on Robust Malware Analysis (WoRMA), 2022.
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Vera Rimmer, Azqa Nadeem, Sicco Verver, Davy Preuveneers, Wouter Joosen
Open-World Network Intrusion Detection." Security and Artificial Intelligence, Springer, p. 254-283, 2022.
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Gints Engelen, Vera Rimmer, Wouter Joosen
Troubleshooting an Intrusion Detection Dataset: The CICIDS2017 Case Study, IEEE Security and Privacy Workshops, Workshop on Traffic Measurement and Classification (WTMC), 2020.
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Vera Rimmer, Davy Preuveneers, Marc Juarez, Tom Van Goethem, Wouter Joosen
Automated Website Fingerprinting through Deep Learning, Network and Distributed System Security Symposium (NDSS), 2018.
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Giuseppe Garofalo, Vera Rimmer, Tim Van hamme, Davy Preuveneers, Wouter Joseen
Fishy Faces: Crafting Adversarial Images to Poison Face Authentication, USENIX Workshop on Offensive Technologies (WOOT), 2018.
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Davy Preuveneers, Vera Rimmer, Ilias Tsingenopolous, Jan Spooren, Wouter Joosen, Elisabeth Ilie-Zudor
Chained Anomaly Detection Models for Federated Learning: An Intrusion Detection Case Study, Applied Sciences, vol. 8, num. 12, p. 1-21, 2018.
Selected Academic Service
- CCS 2024Program committee member (Privacy and Anonymity track)
- ACNS 2024Program committee member
- PETS 2024Program committee member
- PETS 2023Program committee member
- EuroS&P 2023Mentoring chair
- WiSec 2023Program committee member
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EuroS&P 2022Program committee member
Distinguished reviewer award 2022
Posters co-chair - WiSec 2022Program committee member
- PETS 2022External reviewer
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EuroS&P 2021Program committee member Distinguished reviewer award 2021
- WPES 2020Program committee member
- NSPW 2020Program committee member
- EuroS&P 2020Program committee member
- EuroS&P 2019External reviewer
- Selected journalsIEEE TDSC, IEEE TIFS, Computer Networks
Teaching and Mentoring
Teaching Assistance
- Bachelor 2016-2021Computer Architecture and Software Systems.
- Bachelor 2016-2018Object-Oriented Programming
Master Theses (Co-)Supervision
- Joren Van HeckeMethods matter: improving evaluation methodologies for deep learning based Tor website fingerprinting attacks, 2023.
- Sander PrenenEfficient and evasive distributed adversarial attacks using particle swarm optimization, 2022.
- Simon TasEnhancing machine learning for security applications with active learning, 2022.
- Jonathan CraessaertsA more efficient way to detect volumetric attacks using flow aggregation and deep learning, 2022.
- Mattias VanderwegenAttribution of malicious cyber incidents with neural networks, 2022.
- Abel Rodríguez RomeroDeep unsupervised network anomaly detection in real traffic flows, 2020.
- Arno StienaersAdversarial examples against network intrusion detection systems in feature space, 2020.
- Andreas Vande VoordeAutomating black-box adversarial attacks, 2020.
- Rik PauwelsDefenses against black-box adversarial attacks with reinforcement learning, 2020.
- Maarten CraeynestMorphed face generation using generative adversarial networks, 2019.
- Tom GijselinckSecuring self-sovereign identity to prevent impersonation of digital identity, 2019.
- Pieter ClaerhoutAccess control in evolving threat landscapes, 2019.
- Myriam Van ErumInterpretable log analysis with deep learning, 2019.
- Jin LiSequence-based intrusion detection with recurrent neural networks, 2019.
- Nicolas FinnéOpen set recognition of network intrusions, 2018.
- Giuseppe GarofaloExploring poisoning attacks against a face recognition system, 2018.
- Marco FarinettiEvasion attacks against ensemble-learning based behavioral authentication, 2018.