Applying graph-based anomaly detection approaches to thediscovery of insider threats

Authors:
William Eberle;Lawrence Holder
Affiliations:
Department of Computer Science, Tennessee Technological University, Cookeville, TN;School of Electrical Engineering & Computer Science, Washington State University, Pullman, WA
Venue:
ISI'09 Proceedings of the 2009 IEEE international conference on Intelligence and security informatics
Year:
2009

Citing 3
Cited 1

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Graph coarsening for path finding in cybersecurity graphs

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Abstract

The ability to mine data represented as a graph has become important in several domains for detecting various structural patterns. One important area of data mining is anomaly detection, but little work has been done in terms of detecting anomalies in graph-based data. In this paper we present graph-based approaches to uncovering anomalies in applications containing information representing possible insider threat activity: e-mail, cell-phone calls, and order processing.