Sicco Verwer

Sicco Verwer is an Associate Professor in machine learning with applications in cyber security and software engineering at TU Delft since 2014. Before this, he has been a postdoctoral researcher for several years at RU Nijmegen, KU Leuven, and TU Eindhoven.
He has worked on several topics in machine learning and is best known for his work in grammatical inference, i.e., learning state machines from trace data. He has researched and implemented several algorithms for learning such models including RTI, which is one of the first that is able to learn timed automata. In 2013, he received a VENI grant from STW to extend this work and apply it in cyber security. Other recent work include several methods for declarative modelling of machine learning problems using mathematical solvers, and making classifiers discrimination-aware.
He teaches two courses in the cyber security master at TU Delft: Cyber Data Analytics and Automated Software Testing and Reverse Engineering.
If you are interested in the research performed by his lab, or joining as PhD or MSc student, please have a look at Sicco's publications and past publicly available MSc and BSc theses.

  1. A. Nadeem, S.E. Verwer, Stephen Moskal, Shanchieh Jay Yang, Enabling Visual Analytics via Alert-driven Attack Graphs, In CCS 2021 - Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security p.2420-2422, Association for Computing Machinery (ACM).
  2. A. Nadeem, S.E. Verwer, Shanchieh Jay Yang, SAGE: Intrusion Alert-driven Attack Graph Extractor, In 18th IEEE Symposium on Visualization for Cyber Security p.36-41, IEEE.
  3. A. Nadeem, C.A. Hammerschmidt, C. Hernandez Ganan, S.E. Verwer, Beyond Labeling: Using Clustering to Build Network Behavioral Profiles of Malware Families, In Malware Analysis using Artificial Intelligence and Deep Learning p.381-409, Springer.
  4. S.E. Verwer, A. Nadeem, C.A. Hammerschmidt, L. Bliek, Abdullah Al-Dujaili, Una-May O’Reilly, The Robust Malware Detection Challenge and Greedy Random Accelerated Multi-Bit Search, In Workshop on artificial intelligence and security p.61-70, Association for Computing Machinery (ACM).
  5. M.P. Roeling, A. Nadeem, S.E. Verwer, Hybrid connection and host clustering for community detection in spatial-temporal network data, In ECML PKDD 2020 Workshops - Workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases ECML PKDD 2020 Volume 1323 p.178-204.
  6. A. Nadeem, Understanding Adversary Behavior via XAI: Leveraging Sequence Clustering To Extract Threat Intelligence
  7. Louis Gevers, Neil Yorke-Smith, Cooperation in Harsh Environments: The Effects of Noise in Iterated Prisoner's Dilemma, In Proceedings of BNAIC/BeneLearn 2020 p.414-415, RU Leiden.

Dr. S.E. Verwer