Open Access
December 2019 On Bayesian new edge prediction and anomaly detection in computer networks
Silvia Metelli, Nicholas Heard
Ann. Appl. Stat. 13(4): 2586-2610 (December 2019). DOI: 10.1214/19-AOAS1286


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.


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Silvia Metelli. Nicholas Heard. "On Bayesian new edge prediction and anomaly detection in computer networks." Ann. Appl. Stat. 13 (4) 2586 - 2610, December 2019.


Received: 1 May 2019; Revised: 1 July 2019; Published: December 2019
First available in Project Euclid: 28 November 2019

zbMATH: 07160951
MathSciNet: MR4037442
Digital Object Identifier: 10.1214/19-AOAS1286

Keywords: anomaly detection , Bayesian inference , Computer networks , new edges

Rights: Copyright © 2019 Institute of Mathematical Statistics

Vol.13 • No. 4 • December 2019
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