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.
