Terrorism informatics has been defined as the application of advanced methodologies, information fusion and analysis techniques to acquire, integrate process, analyze, and manage the diversity of terrorism-related information for international and homeland security-related applications. The wide variety of methods used in terrorism informatics are derived from Computer Science, Informatics, Statistics, Mathematics, Linguistics, Social Sciences, and Public Policy and these methods are involved in the collection of huge amounts of information from varied and multiple sources and of many types in numerous languages. Information fusion and information technology analysis techniques-which include data mining, data integration, language translation technologies, and image and video processing-play central roles in the prevention, detection, and remediation of terrorism.

Terrorism Informatics: Knowledge Management and Data Mining for Homeland Security will provide an interdisciplinary and comprehensive survey of the state-of-the-art in the terrorism informatics domain along three basic dimensions: methodological issues in terrorism research; information infusion techniques to support terrorism prevention, detection, and response; and legal, social, privacy, and data confidentiality challenges and approaches. Featuring contributions by leading researchers and practitioners, illustrative case studies, and applications of terrorism informatics techniques, the book will be an essential resource for scientists, security professionals, counterterrorism experts, and policy makers.