An Advanced System for Modeling Asymmetric Threats
Satnam Singh, William Donat, Haiying Tu, Jijun Lu, Krishna Rao Pattipati, Peter Willett · 2006
In this paper, we introduce an advanced software tool for modeling asymmetric threats, the Adaptive Safety Analysis and Monitoring (ASAM) system. The ASAM system is a hybrid model-based system for assisting intelligence analysts to identify asymmetric threats, to predict possible evolution of the suspicious activities, and to suggest strategies for countering threats. It employs a novel combination of hidden Markov models (HMMs) and Bayesian networks (BNs) to compute the likelihood that a certain threat exists. It provides a distributed processing structure for gathering, sharing, understanding, and using information to assess and predict adversary network states. We illustrate the capabilities of the ASAM system by way of application to a hypothetical model of development of nuclear weapons program by an unknown hostile country. The simulation results show that the ASAM system is able to detect the modeled pattern with a high performance (greater than 95% clutter suppression capability).