Terrorism threat assessment with multi-module Bayesian network

doi:10.7523/j.issn.2095-6134.2015.02.017

Abstract

Abstract:

This study intends to provide decision support for counter-terrorism according to the threat of terrorist attacks. Because of the diversity, uncertainty, and ambiguity of assessment information about terrorist attacks, Bayesian network is proposed to assess threat from the consequence of attacks. This study presents a multi-module Bayesian network threat assessment model for the complexity of the terrorist attacks, and this model combines the qualitative and quantitative assessment. We study the multi-module Bayesian network structure learning, parameter learning, and inference. Finally we compute the terrorism threat degree and conduct instance analysis. Simulation results show that this model effectively assesses the real threat degree of terrorist attacks.

Key words: terrorist attacks, threat assessment, multi-module, Bayesian network, inference

CLC Number:

TP399

WEI Jing, WANG Juyun, YU Hua. Terrorism threat assessment with multi-module Bayesian network[J]. , 2015, 32(2): 264-272.

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