Practical algorithms for subgroup detection in covert networks

Authors:
Nasrullah Memon;Uffe Kock Wiil;Pir Abdul Rasool Qureshi
Affiliations:
The Maersk Mc-Kinney Moller Institute, University of Denmark, Campusvej 55, 5230 Odense M, Denmark.;The Maersk Mc-Kinney Moller Institute, University of Denmark, Campusvej 55, 5230 Odense M, Denmark.;The Maersk Mc-Kinney Moller Institute, University of Denmark, Campusvej 55, 5230 Odense M, Denmark
Venue:
International Journal of Business Intelligence and Data Mining
Year:
2010

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Abstract

In this paper, we present algorithms for subgroup detection and demonstrated them with a real-time case study of USS Cole bombing terrorist network. The algorithms are demonstrated in an application by a prototype system. The system finds associations between terrorist and terrorist organisations and is capable of determining links between terrorism plots occurred in the past, their affiliation with terrorist camps, travel record, funds transfer, etc. The findings are represented by a network in the form of an Attributed Relational Graph (ARG). Paths from a node to any other node in the network indicate the relationships between individuals and organisations. The system also provides assistance to law enforcement agencies, indicating when the capture of a specific terrorist will more likely destabilise the terrorist network. In this paper, we discuss the important application area related to subgroups in a terrorist cell using filtering of graph algorithms. The novelty of the algorithms can be easily found from the results they produce.