EWAS: Modeling application for early detection of terrorist threats

Abstract

This paper presents a model and system architecture for an early warning system to detect terrorist threats. The paper discusses the shortcomings of state-of-the-art systems and outlines the functional requirements that must to be met by an ideal system working in the counterterrorism domain. The concept of generation of early warnings to predict terrorist threats is presented. The model relies on data collection from open data sources, information retrieval, information extraction for preparing structured workable data sets from available unstructured data, and finally detailed investigation. The conducted investigation includes social network analysis, investigative data mining, and heuristic rules for the study of complex covert networks for terrorist threat indication. The presented model and system architecture can be used as a core framework for an early warning system. © 2010 Springer-Verlag Wien.