SoK: Explainable Machine Learning for Computer Security Applications

1 code implementation • 22 Aug 2022 • Azqa Nadeem, Daniël Vos, Clinton Cao, Luca Pajola, Simon Dieck, Robert Baumgartner, Sicco Verwer

The security literature sometimes also fails to disentangle the role of the various stakeholders, e. g., by providing explanations to model users and designers while also exposing them to adversaries.

Computer Security Explainable artificial intelligence +1

SECLEDS: Sequence Clustering in Evolving Data Streams via Multiple Medoids and Medoid Voting

1 code implementation • 24 Jun 2022 • Azqa Nadeem, Sicco Verwer

K-medoids or Partitioning Around Medoids (PAM) is commonly used to cluster sequences since it supports alignment-based distances, and the k-centers being actual data items helps with cluster interpretability.

Clustering Dynamic Time Warping

Robust Attack Graph Generation

no code implementations • 15 Jun 2022 • Dennis Mouwen, Sicco Verwer, Azqa Nadeem

We present a method to learn automaton models that are more robust to input modifications.

Graph Generation

SAGE: Intrusion Alert-driven Attack Graph Extractor

1 code implementation • 6 Jul 2021 • Azqa Nadeem, Sicco Verwer, Shanchieh Jay Yang

We propose to automatically learn AGs based on actions observed through intrusion alerts, without prior expert knowledge.