Azqa Nadeem (2024), Cybersecurity as a Crosscutting Concept Across an Undergrad Computer Science Curriculum: An Experience Report, In SIGCSE 2024 - Proceedings of the 55th ACM Technical Symposium on Computer Science Education p.916-922, Association for Computing Machinery (ACM).

A. Nadeem (2024), Understanding Adversary Behavior via XAI: Leveraging Sequence Clustering To Extract Threat Intelligence, PhD Thesis Delft University of Technology.

A. Nadeem, S.E. Verwer, Shanchieh Jay Yang (2023), Learning About the Adversary, Alexander Kott (Eds.), In Autonomous Intelligent Cyber Defense Agent (AICA) p.105-132, Springer.

Azqa Nadeem, Sicco Verwer (2023), SECLEDS: Sequence Clustering in Evolving Data Streams via Multiple Medoids and Medoid Voting, Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas (Eds.), In Machine Learning and Knowledge Discovery in Databases. p.157-173, Springer.

Azqa Nadeem, Daniël Vos, Clinton Cao, Luca Pajola, Simon Dieck, Robert Baumgartner, Sicco Verwer (2023), SoK: Explainable Machine Learning for Computer Security Applications, Lisa O’Conner (Eds.), In Proceedings of the 2023 IEEE 8th European Symposium on Security and Privacy (EuroS&P) p.221-240, IEEE.

A. Nadeem, S.E. Verwer, Stephen Moskal, Shanchieh Jay Yang (2022), Alert-driven Attack Graph Generation using S-PDFA, In IEEE Transactions on Dependable and Secure Computing Volume 19 p.731-746.

A. Nadeem, Vera Rimmer, Joosen Wouter, S.E. Verwer (2022), Intelligent Malware Defenses, In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) p.217-253, Springer.

Vera Rimmer, Azqa Nadeem, Sicco Verwer, Davy Preuveneers, Wouter Joosen (2022), Open-World Network Intrusion Detection, In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) p.254-283, Springer.

A. Nadeem, C.A. Hammerschmidt, C. Hernandez Ganan, S.E. Verwer (2021), Beyond Labeling: Using Clustering to Build Network Behavioral Profiles of Malware Families, Andrii Shalaginov, Mark Stamp, Mamoun Alazab (Eds.), In Malware Analysis using Artificial Intelligence and Deep Learning p.381-409, Springer.

A. Nadeem, S.E. Verwer, Stephen Moskal, Shanchieh Jay Yang (2021), 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).