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.
|Tidsskrift||International Journal of Business Intelligence and Data Mining|
|Status||Udgivet - 2010|