Analyzing the effectiveness of graph metrics for anomaly detection in online social networks

Hassanzadeh, Reza, Nayak, Richi, & Stebila, Douglas (2012) Analyzing the effectiveness of graph metrics for anomaly detection in online social networks. Lecture Notes in Computer Science : Web Information Systems Engineering, 7651, pp. 624-630.

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Online social networks can be modelled as graphs; in this paper, we analyze the use of graph metrics for identifying users with anomalous relationships to other users. A framework is proposed for analyzing the effectiveness of various graph theoretic properties such as the number of neighbouring nodes and edges, betweenness centrality, and community cohesiveness in detecting anomalous users. Experimental results on real-world data collected from online social networks show that the majority of users typically have friends who are friends themselves, whereas anomalous users’ graphs typically do not follow this common rule. Empirical analysis also shows that the relationship between average betweenness centrality and edges identifies anomalies more accurately than other approaches.

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ID Code: 57995
Item Type: Journal Article
Refereed: Yes
Additional Information: Paper presented in Web Information Systems Engineering - WISE 2012
13th International Conference, Paphos, Cyprus, November 28-30, 2012.
Additional URLs:
Keywords: Anomaly detection, Graph mining, Data mining, Online social networks
DOI: 10.1007/978-3-642-35063-4_45
ISBN: 978-3-642-35063-4
ISSN: 1611-3349
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > Institutes > Institute for Future Environments
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2012 Springer-Verlag Berlin Heidelberg
Copyright Statement: Conference proceedings published by Springer Verlag will be available via SpringerLink.
Deposited On: 12 Mar 2013 01:10
Last Modified: 15 Mar 2013 01:06

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