Paper
15 September 2004 The adaptive safety analysis and monitoring system
Haiying Tu, Jeffrey Allanach, Satnam Singh, Krishna R. Pattipati, Peter Willett
Author Affiliations +
Abstract
The Adaptive Safety Analysis and Monitoring (ASAM) system is a hybrid model-based software tool for assisting intelligence analysts to identify terrorist threats, to predict possible evolution of the terrorist activities, and to suggest strategies for countering terrorism. The ASAM system provides a distributed processing structure for gathering, sharing, understanding, and using information to assess and predict terrorist network states. In combination with counter-terrorist network models, it can also suggest feasible actions to inhibit potential terrorist threats. In this paper, we will introduce the architecture of the ASAM system, and discuss the hybrid modeling approach embedded in it, viz., Hidden Markov Models (HMMs) to detect and provide soft evidence on the states of terrorist network nodes based on partial and imperfect observations, and Bayesian networks (BNs) to integrate soft evidence from multiple HMMs. The functionality of the ASAM system is illustrated by way of application to the Indian Airlines Hijacking, as modeled from open sources.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Haiying Tu, Jeffrey Allanach, Satnam Singh, Krishna R. Pattipati, and Peter Willett "The adaptive safety analysis and monitoring system", Proc. SPIE 5403, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense III, (15 September 2004); https://doi.org/10.1117/12.536474
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Cited by 10 scholarly publications.
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KEYWORDS
Systems modeling

Data modeling

Process modeling

Safety

Stochastic processes

Sensors

Signal detection

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