Scholion.ai

On Bayesian new edge prediction and anomaly detection in computer networks

Silvia Metelli, Nicholas Heard

The Annals of Applied Statistics · 2019 · Volume 13 · Issue 4

DOI: 10.1214/19-AOAS1286

Abstract

Monitoring computer network traffic for anomalous behaviour presents an important security challenge. Arrivals of new edges in a network graph represent connections between a client and server pair not previously observed, and in rare cases these might suggest the presence of intruders or malicious implants. We propose a Bayesian model and anomaly detection method for simultaneously characterising existing network structure and modelling likely new edge formation. The method is demonstrated on real computer network authentication data and successfully identifies some machines which are known to be compromised.

Keywords

anomaly detection, Bayesian inference, Computer networks, new edges

Enable JavaScript for citation tools and additional paper interactions.