How Investigative Data Mining Can Help Intelligence Agencies to Discover Dependence of Nodes in Terrorist Networks

Authors:
Nasrullah Memon;David L. Hicks;Henrik Legind Larsen
Affiliations:
Department of Computer Science and Engineering, Esbjerg Institute of Technology, Aalborg University, Niels Bohrs Vej 8, DK-6700, Esbjerg, Denmark;Department of Computer Science and Engineering, Esbjerg Institute of Technology, Aalborg University, Niels Bohrs Vej 8, DK-6700, Esbjerg, Denmark;Department of Computer Science and Engineering, Esbjerg Institute of Technology, Aalborg University, Niels Bohrs Vej 8, DK-6700, Esbjerg, Denmark
Venue:
ADMA '07 Proceedings of the 3rd international conference on Advanced Data Mining and Applications
Year:
2007

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Abstract

A new model of dependence centrality is proposed. The centrality measure is based on shortest paths between the pair of nodes. We apply this measure with the demonstration of a small network example. The comparisons are made with betweenness centrality. We discuss how intelligence investigation agencies could benefit from the proposed measure. In addition to that we argue about the investigative data mining techniques we are using, and a comparison is provided with traditional data mining techniques.