The ability of terrorist networks to conduct
sophisticated and simultaneous attacks – the most recent
one on March 11, 2004 in Madrid, Spain – suggests that
there is a significant need for developing information
technology tools for counter-terrorism analysis. These
technologies could empower intelligence analysts to find
information faster, share, and collaborate across
agencies, "connect the dots" better, and conduct quicker
and better analyses. One such technology, the Adaptive
Safety Analysis and Monitoring (ASAM) system, is under
development at the University of Connecticut. In this
paper, the ASAM system is introduced and its capabilities
are discussed. The vulnerabilities at the Athens 2004
Olympics are modeled and patterns of anomalous
behavior are identified using a combination of featureaided
multiple target tracking, hidden Markov models
(HMMs), and Bayesian networks (BNs). Functionality of
the ASAM system is illustrated by way of application to
two hypothetical models of terrorist activities at the
Athens 2004 Olympics.*