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An Application of Bayesian Networks to Antiterrorism Risk Management for Military Planners

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dc.contributor.author Hudson, Linwood D.
dc.contributor.author Ware, Bryan S.
dc.contributor.author Laskey, Kathryn B.
dc.contributor.author Mahoney, Suzanne M.
dc.date.accessioned 2005-11-18T20:51:11Z
dc.date.available 2005-11-18T20:51:11Z
dc.date.issued 2005-11-18T20:51:11Z
dc.identifier.other 01
dc.identifier.uri https://hdl.handle.net/1920/268
dc.description.abstract Recent events underscore the need for effective tools for managing the risks posed by terrorists. Assessing the threat of terrorist attack requires combining information from multiple disparate sources, most of which involve intrinsic and irreducible uncertainties. This paper describes Site Profiler® Installation Security Planner, a tool initially built to assist antiterrorism planners at military installations to draw inferences about the risk of terrorist attack. Site Profiler applies knowledge-based Bayesian network construction to allow users to manage a portfolio of hundreds of threat/asset pairs. The constructed networks combine evidence from analytic models, simulations, historical data, and user judgments. Site Profiler was constructed using our generic application development environment that combines a dynamically generated object model, a Bayesian inference engine, a graphical editor for defining the object model, and persistent storage for a knowledge base of Bayesian network fragment objects. Site Profiler's human-computer interaction system is tailored to mathematically unsophisticated users. Future extensions to Site Profiler will use data warehousing to allow analysis and validation of the network’s ability to predict the most effective antiterrorism risk management solutions.
dc.format.extent 751841 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US en
dc.relation.ispartofseries C4I-05-01
dc.subject Bayesian networks en_US
dc.subject Terrorism prevention en_US
dc.subject risk management en_US
dc.subject military en_US
dc.title An Application of Bayesian Networks to Antiterrorism Risk Management for Military Planners en
dc.type Article en


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