Covert network analysis to detect key players using correlation and social network analysis

The increasing terrorist events across all over the world have attracted the attention of many researchers towards counter-terrorism. This field demands from them to contribute in developing new techniques and methods for analysis, identification and prediction of terrorist events and group leaders. In this paper, we propose a model to detect key players from a network keeping focus on their communication contents. The proposed model finds correlation of communication contents of all nodes with data dictionary and detects nodes based on a threshold correlation value. A new network is drawn and its density is calculated. After that different centrality measures are applied on new network and most important nodes detected using each measure. That gives us different key players with different roles in the network. Data dictionary consists of words or terms used by the terrorist in their communication. We used Enron email data set to test and validate our proposed model.