Azqa Nadeem


04.E.360, Building 28, EEMCS,

Delft University of Technology,

The Netherlands

I am a Ph.D. candidate and Lecturer in the Cyber Analytics Lab (Cyber Security group) at Delft University of Technology, advised by Dr. Sicco Verwer.

My research focuses on Explainable Machine Learning for Cyber Security. I truly believe that machine learning can provide more insights than just prediction probabilities. To this aim, I develop explainable sequential machine learning pipelines that extract actionable intelligence from large volumes of cyber data with the aim of assisting security analysts in their daily operations. These pipelines create human in the loop settings for AI-assisted humans.

Next to research, I spend 40% of my time developing and teaching Cyber Security lectures to BSc. (Computer Science and Engineering) students at TU Delft. The teaching material can be found under Cyber Security Lecture Series.

Outside of work, I love landscape photography and traveling. I enjoy discussions about human psychology, devious behavior, cats, imposter syndrome, and… well… cats.

Recent news

05-2023 Submitted the first draft of my thesis to my promotor! :muscle: :sparkles:
04-2023 Won the “Best Demo Award” for our alert-driven attack graph generator at ICT.Open 2023! :trophy: :gift:
04-2023 Teaching cybersecurity to the Executive MSc. students at Leiden University. :woman_teacher:
03-2023 Hosted WICCA for a meetup for Women in Cybersecurity on “Cybersecurity in the AI age”.
02-2023 Our SoK paper on XAI for cybersecurity has been accepted at EuroS&P! :scroll:

Selected publications

  1. EuroS&P
    SoK: Explainable Machine Learning for Computer Security Applications
    Nadeem, Azqa, Vos, Daniel, Cao, Clinton, Pajola, Luca, Dieck, Simon, Baumgartner, Robert, and Verwer, Sicco
    In IEEE European Symposium on Security and Privacy (Euro S&P), 2023
  2. ECML
    SECLEDS: Sequence Clustering in Evolving Data Streams via Multiple Medoids
    and Medoid Voting
    Nadeem, Azqa, and Verwer, Sicco
    In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), 2022
  3. TDSC
    Alert-driven Attack Graph Generation using S-PDFA
    Nadeem, Azqa, Verwer, Sicco, Moskal, Stephen, and Yang, Shanchieh J
    In IEEE Transcations on Dependable and Secure Computing, 2021
    Beyond Labeling: Using Clustering to Build Network Behavioral Profiles of
    Malware Families
    Nadeem, Azqa, Hammerschmidt, Christian, Ganan, Carlos H, and Verwer, Sicco
    In Malware Analysis Using Artificial Intelligence and Deep Learning, 2021
  5. CCS
    Enabling Visual Analytics via Alert-driven Attack Graphs
    Nadeem, Azqa, Verwer, Sicco, Moskal, Stephen, and Yang, Shanchieh J
    In Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security, 2021