Title
Practical Approaches for Analysis, Visualization and Destabilizing Terrorist Networks
Abstract
Traditionally most of the literature in social network analysis (SNA) has focused on networks of individuals. Although SNA is not conventionally considered as a data mining technique, it is especially suitable for mining a large volume of association data to discover hidden structural patterns in terrorist networks. After September 11 attacks, SNA has increasingly been used to study terrorist networks. As these covert networks share some features with conventional networks, they are harder to identify because they mask their transactions. The most complicating factor is that terrorist networks are often embedded in a much larger population (i.e., adversaries have links with both covert and innocent individuals). Hence, it is desirable to have tools to correctly classify individuals in covert networks so that the resources for isolating them will be used more efficiently. This paper uses centrality measures from complex networks to discuss how to destabilize adversary networks. We propose newly introduced algorithms for constructing hierarchy of the covert networks, so that investigators can view the structure of the ad hoc networks/ atypical organizations, in order to destabilize the adversaries. The algorithms are also demonstrated by using publicly available dataset. Moreover we also demonstrate techniques for filtering graphs (networks) /detecting particular cells in adversary networks using a fictitious dataset.
Year
DOI
Venue
2006
10.1109/ARES.2006.95
ARES
Keywords
DocType
ISBN
association data,terrorist network,atypical organization,fictitious dataset,destabilizing terrorist networks,practical approaches,adversary network,covert network,centrality measure,complex network,data mining technique,available dataset,terrorism,social network analysis,data visualisation,data mining,ad hoc network,computer networks
Conference
0-7695-2567-9
Citations 
PageRank 
References 
9
1.15
1
Authors
2
Name
Order
Citations
PageRank
Nasrullah Memon150456.67
Henrik Legind Larsen254545.16