Information-Fusion based Indication & Warning Assessment and Recognition System (IIWARS)

The aim of this project is to develop, build and validate an Information-Fusion based Indication & Warning Assessment and Recognition System (IIWARS) focused on asymmetric threats. The proposed system would integrate intelligent information processingtechnologies (for detecting and predicting threat trends), data and model fusion (to merge multiple data sources and multiple predictions), and an optimization framework (for optimal response evaluation). The system would ultimately facilitate robust andcost-effective detection and management of Indications and Warnings. The Phase I effort will (i) establish IIWARS requirements, (ii) design the IIWARS architecture, (iii) develop and demonstrate prototype IIWARS software. The Phase II project will hardenthe software and demonstrate its benefits on focused intelligence applications. Key innovations include: (i) Knowledge Engineering Methods to characterize Indicators and Warning Dimensions, (ii) Knowledge Discovery paradigms (text and data mining) thathelp in early identification of emerging Threats, (iii) Efficient Fusion Mechanisms that can extract and merge features from multiple disparate information sources, (iv) Predictive Models for Threat Estimation by threat source for the Indicators andWarning Dimensions, and (v) Stochastic Optimization Framework for Optimal Response Targeting. Specifically, the most significant benefit of IIWARS is that it will provide access to sophisticated technology to a wide audience of potential users in themilitary intelligence community so that the the power of these technologies will be rapidly exploited/realized for enhanced national security against assymetric threats. IIWARS will have a wide range of important defense and commercial applicationsincluding terrorist threat detection, industrial espionage detection, financial fraud detection, and business intelligence.