5 papers
On fair and realistic performance evaluations for graph-based lateral movement detectors
Corentin Larroche
Research on lateral movement detection has made significant progress in recent years, spurred by the widespread availability of benchmark datasets that make evaluating detectors pr…
Designing a reliable lateral movement detector using a graph foundation model
Corentin Larroche
Foundation models have recently emerged as a new paradigm in machine learning (ML). These models are pre-trained on large and diverse datasets and can subsequently be applied to va…
A source separation approach to temporal graph modelling for computer networks
Corentin Larroche
Detecting malicious activity within an enterprise computer network can be framed as a temporal link prediction task: given a sequence of graphs representing communications between…
Multilayer Block Models for Exploratory Analysis of Computer Event Logs
Corentin Larroche
We investigate a graph-based approach to exploratory data analysis in the context of network security monitoring. Given a possibly large batch of event logs describing ongoing acti…
Dynamically Modelling Heterogeneous Higher-Order Interactions for Malicious Behavior Detection in Event Logs
Corentin Larroche, Johan Mazel, Stephan Clémençon
Anomaly detection in event logs is a promising approach for intrusion detection in enterprise networks. By building a statistical model of usual activity, it aims to detect multipl…