Investigative Data Mining Toolkit: A Software Prototype for Visualizing, Analyzing and Destabilizing Terrorist Networks

Knowledge about the structure and organization of terrorist networks is important for both terrorism investigation and the development of effective strategies to prevent terrorists’ attacks. However, except for network visualization, terrorist network analysis remains primarily a manual process. Existing tools do not provide advanced structural analysis techniques that allow extraction of network knowledge from large volumes of criminal-justice data. It is a well known fact that terrorist activities consist of dispersed organizations (like non-hierarchical organizations), small groups, and individuals who communicate, coordinate and conduct their campaign in a network-like manner. There is a pressing need to automatically collect data of terrorist networks, analyze such networks to find hidden relations and groups, prune datasets to locate regions of interest, find key players, characterize the structure, trace point of vulnerability, and detect efficiency of the network. To meet this challenge, we designed and developed a knowledgebase for storing and manipulating data collected from various authenticated websites. This paper presents framework of investigative data mining toolkit, our recently introduced techniques and algorithms (which are implemented in the investigative data mining toolkit) could be useful for law enforcement agencies that need to analyze terrorist networks and prioritize their targets. Applying recently introduced algorithms for constructing hidden hierarchy of non-hierarchical terrorist networks, we present case studies of the terrorist attacks that occurred in past, in order to construct command structure of the networks.