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A Link Prediction Approach to Anomalous Email Detection

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2 Author(s)
Zan Huang ; Department of Supply Chain and Information Systems, the Smeal College of Business, Pennsylvania State University, University Park, PA 16802 USA e-mail: zanhuang@psu.edu ; Daniel D. Zeng

In many security informatics applications, it is important to monitor traffic over various communication channels and efficiently identify those communications that are unusual for further investigation. This paper studies such anomaly detection problems using a graph-theoretic link prediction approach. Data from the publicly-available Enron email corpus were used to validate the proposed approach.

Published in:

2006 IEEE International Conference on Systems, Man and Cybernetics  (Volume:2 )

Date of Conference:

8-11 Oct. 2006