Ebook: Computational Methods for Counterterrorism

Modern terrorist networks pose an unprecedented threat to international security. Their fluid and non-hierarchical structures, their religious and ideological motivations, and their predominantly non-territorial objectives all radically complicate the question of how to neutralize them. As governments and militaries work to devise new policies and doctrines to combat terror, new technologies are desperately needed to make these efforts effective.

This book collects a wide range of the most current computational research addressing critical issues for counterterrorism in a dynamic and complex threat environment:

• finding, summarizing, and evaluating relevant information from large and dynamic data stores;
• simulation and prediction of likely enemy actions and the effects of proposed counter-efforts; and
• producing actionable intelligence by finding meaningful patterns hidden in masses of noisy data items.

The contributions are organized thematically into four sections. The first section concerns efforts to provide effective access to small amounts of relevant information buried in enormous amounts of diverse unstructured data. The second section discusses methods for the key problem of extracting meaningful information from digitized documents in various languages. The third section presents research on analyzing graphs and networks, offering new ways of discovering hidden structures in data and profiles of adversaries’ goals and intentions. Finally, the fourth section of the book describes software systems that enable analysts to model, simulate, and predict the effects of real-world conflicts.

The models and methods discussed in this book are invaluable reading for governmental decision-makers designing new policies to counter terrorist threats, for members of the military, intelligence, and law enforcement communities devising counterterrorism strategies based on new technologies, and for academic and industrial researchers devising more effective methods for knowledge discovery in complicated and diverse datasets.

Modern terrorist networks pose an unprecedented threat to international security. The question of how to neutralize that threat is complicated radically by their fluid, non-hierarchical structures, religious and ideological motivations, and predominantly non-territorial objectives. Governments and militaries are crafting new policies and doctrines to combat terror, but they desperately need new technologies to make these efforts effective.

This book collects a wide range of the most current computational research that addresses critical issues for countering terrorism, including:

• Finding, summarizing, and evaluating relevant information from large and changing data stores;
• Simulating and predicting enemy acts and outcomes; and
• Producing actionable intelligence by finding meaningful patterns hidden in huge amounts of noisy data.

The book’s four sections describe current research on discovering relevant information buried in vast amounts of unstructured data; extracting meaningful information from digitized documents in multiple languages; analyzing graphs and networks to shed light on adversaries’ goals and intentions; and developing software systems that enable analysts to model, simulate, and predict the effects of real-world conflicts.

The research described in this book is invaluable reading for governmental decision-makers designing new policies to counter terrorist threats, for members of the military, intelligence, and law enforcement communities devising counterterrorism strategies, and for researchers developing more effective methods for knowledge discovery in complicated and diverse datasets.