| SoK: Explainable machine learning for computer security applications A Nadeem, D Vos, C Cao, L Pajola, S Dieck, R Baumgartner, S Verwer 2023 IEEE 8th European Symposium on Security and Privacy (EuroS&P), 221-240, 2023 | 66 | 2023 |
| Alert-driven attack graph generation using S-PDFA A Nadeem, S Verwer, S Moskal, SJ Yang IEEE Transactions on Dependable and Secure Computing 19 (2), 731-746, 2021 | 61 | 2021 |
| SAGE: Intrusion Alert-driven Attack Graph Extractor A Nadeem, S Verwer, SJ Yang IEEE Symposium on Visualization for Cyber Security (VizSec), 36-41, 2021 | 23 | 2021 |
| Beyond Labeling: Using Clustering to Build Network Behavioral Profiles of Malware Families A Nadeem, C Hammerschmidt, CH Gañán, S Verwer Malware Analysis Using Artificial Intelligence and Deep Learning, 381-409, 2021 | 20* | 2021 |
| Enabling visual analytics via alert-driven attack graphs A Nadeem, S Verwer, S Moskal, SJ Yang Proceedings of the 2021 ACM SIGSAC conference on computer and communications …, 2021 | 15 | 2021 |
| The robust malware detection challenge and greedy random accelerated multi-bit search S Verwer, A Nadeem, C Hammerschmidt, L Bliek, A Al-Dujaili, ... Proceedings of the 13th ACM Workshop on Artificial Intelligence and Security …, 2020 | 13 | 2020 |
| Open-world network intrusion detection V Rimmer, A Nadeem, S Verwer, D Preuveneers, W Joosen Security and artificial intelligence: A crossdisciplinary approach, 254-283, 2022 | 9 | 2022 |
| Investigating type declaration mismatches in Python L Pascarella, A Ram, A Nadeem, D Bisesser, N Knyazev, A Bacchelli 2018 IEEE Workshop on Machine Learning Techniques for Software Quality …, 2018 | 8 | 2018 |
| Intelligent malware defenses A Nadeem, V Rimmer, W Joosen, S Verwer Security and artificial intelligence: A crossdisciplinary approach, 217-253, 2022 | 5 | 2022 |
| SECLEDS: sequence clustering in evolving data streams via multiple medoids and medoid voting A Nadeem, S Verwer Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022 | 4 | 2022 |
| Clustering malware’s network behavior using simple sequential features A Nadeem, CH Ganán, S Verwer Delft University of Technology, 2018 | 4 | 2018 |
| Understanding adversary behavior via XAI: Leveraging sequence clustering to extract threat intelligence A Nadeem Ph. D. Thesis, 2024 | 2 | 2024 |
| Critical Path Prioritization Dashboard for Alert-driven Attack Graphs SL Díaz, S Pastrana, A Nadeem arXiv preprint arXiv:2310.13079, 2023 | 2 | 2023 |
| Robust Attack Graph Generation D Mouwen, S Verwer, A Nadeem Learning and Automata (LearnAut), 2022 | 2 | 2022 |
| Adaptive cache mode selection for queries over raw data T Azim, A Nadeem, A Ailamaki Ninth International Workshop on Accelerating Analytics and Data Management …, 2018 | 2 | 2018 |
| Cybersecurity as a Crosscutting Concept Across an Undergrad Computer Science Curriculum: An Experience Report A Nadeem Proceedings of the ACM SIGCSE Technical Symposium on Computer Science …, 2024 | 1 | 2024 |
| Learning about the adversary A Nadeem, S Verwer, SJ Yang Autonomous Intelligent Cyber Defense Agent (AICA) A Comprehensive Guide, 105-132, 2023 | 1 | 2023 |
| Critical Path Exploration Dashboard for Alert-driven Attack Graphs 🏆 A Nadeem, SL Dıaz, S Verwer IEEE Symposium on Visualization for Cyber Security (VizSec), 2022 | 1* | 2022 |
| MalPaCA Feature Engineering-A comparative analysis between automated feature engineering and manual feature engineering on network traffic S kyung Park, A Nadeem, S Verwer | 1 | 2021 |
| Hybrid connection and host clustering for community detection in spatial-temporal network data MP Roeling, A Nadeem, S Verwer ECML PKDD 2020 Workshops: Workshops of the European Conference on Machine …, 2020 | 1 | 2020 |
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