Paper Info
Title
Link-Based Anomaly Detection in Communication Networks
Abstract
Communication networks, such as networks formed by phone calls and email communications, can be modeled as dynamic graphs with vertices representing agents and edges representing communications. Anomaly detection is to identify abnormal behaviour occurring in these networks. This is crucial for anti-terrorism, resource allocation and network management. The contents of the communications are often unavailable or protected by regulations or encryption, which makes linkage information the only type of data we can rely on in order to identify anomalies. In this paper, we propose a link-based anomaly detection method that considers deviations from individual patterns by taking into account the behaviour pattern of the cluster to which the individual belongs. Clusters can be formed by a standard clustering procedure or based on a specific attribute depending on the dataset. Experiments show that this method performs well on both network traffic and email communication data.
Year
DOI
Venue
2008
10.1109/WIIAT.2008.91
Web Intelligence/IAT Workshops
Keywords
Field
DocType
anomaly detection,network management,individual pattern,communication networks,email communication,network traffic,link-based anomaly detection,abnormal behaviour,email communication data,behaviour pattern,link-based anomaly detection method,communication network,feature extraction,covariance matrix,couplings
Data mining,Anomaly detection,Telecommunications network,Computer science,Computer network,Feature extraction,Encryption,Resource allocation,Covariance matrix,Cluster analysis,Network management
Conference
Citations 
PageRank 
References 
2
0.41
3
Authors
4
Name
Order
Citations
PageRank
Xiaomeng Wan180.86
Evangelos Milios23073360.46
Nauzer Kalyaniwalla3312.68
Jeannette Janssen429532.23