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Haiying Tu

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Proceedings Article | 15 September 2004 Paper

The adaptive safety analysis and monitoring system

Haiying Tu, Jeffrey Allanach, Satnam Singh, Krishna Pattipati, Peter Willett

Proceedings Volume 5403, (2004) https://doi.org/10.1117/12.536474

KEYWORDS: Systems modeling, Safety, Process modeling, Stochastic processes, Data modeling, Weapons, Sensors, Signal detection, Network architectures, Statistical modeling

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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.

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