A link prediction approach to anomalous email detection

Zan Huang, Daniel D. Zeng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

33 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publication2006 IEEE International Conference on Systems, Man and Cybernetics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1131-1136
Number of pages6
ISBN (Print)1424401003, 9781424401000
DOIs
StatePublished - Jan 1 2006
Event2006 IEEE International Conference on Systems, Man and Cybernetics - Taipei, Taiwan, Province of China
Duration: Oct 8 2006Oct 11 2006

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume2
ISSN (Print)1062-922X

Other

Other2006 IEEE International Conference on Systems, Man and Cybernetics
CountryTaiwan, Province of China
CityTaipei
Period10/8/0610/11/06

ASJC Scopus subject areas

  • Engineering(all)

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    Huang, Z., & Zeng, D. D. (2006). A link prediction approach to anomalous email detection. In 2006 IEEE International Conference on Systems, Man and Cybernetics (pp. 1131-1136). [4274000] (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics; Vol. 2). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSMC.2006.384552