Detecting Hidden Hierarchy in Terrorist Networks: Some Case Studies

Authors:
Nasrullah Memon;Henrik Legind Larsen;David L. Hicks;Nicholas Harkiolakis
Affiliations:
The European Center for Counterterrorism Research and Studies Department of Computer Science and Engineering, Aalborg University, Esbjerg, Denmark DK-6700 and Hellenic American University, Athens ...;The European Center for Counterterrorism Research and Studies Department of Computer Science and Engineering, Aalborg University, Esbjerg, Denmark DK-6700;The European Center for Counterterrorism Research and Studies Department of Computer Science and Engineering, Aalborg University, Esbjerg, Denmark DK-6700;Hellenic American University, Athens Campus, Greece
Venue:
PAISI, PACCF and SOCO '08 Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics
Year:
2008

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Abstract

This paper provides a novel algorithm to automatically detect the hidden hierarchy in terrorist networks. The algorithm is based on centrality measures used in social network analysis literature. The advantage of such automatic methods is to detect key players in terrorist networks. We illustrate the algorithm over some case studies of terrorist events that have occurred in the past. The results show great promise in detecting high value individuals.