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

ENCODE: Encoding NetFlows for Network Anomaly Detection

1 code implementation • 8 Jul 2022 • Clinton Cao, Annibale Panichella, Sicco Verwer, Agathe Blaise, Filippo Rebecchi

The first step for these machine learning pipelines is to pre-process the data before it is given to the machine learning algorithm.

Anomaly Detection BIG-bench Machine Learning

Learning State Machines to Monitor and Detect Anomalies on a Kubernetes Cluster

no code implementations • 28 Jun 2022 • Clinton Cao, Agathe Blaise, Sicco Verwer, Filippo Rebecchi

In this work, we propose an approach that learns state machine models to model the runtime behaviour of a cloud environment that runs multiple microservice applications.