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Modeling and Risk Analysis of Chemical Terrorist Attacks: A Bayesian Network Method

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  • Rongchen Zhu

    (School of Information Technology and Network Security, People’s Public Security University of China, Beijing 102628, China)

  • Xiaofeng Hu

    (School of Information Technology and Network Security, People’s Public Security University of China, Beijing 102628, China)

  • Xin Li

    (School of Information Technology and Network Security, People’s Public Security University of China, Beijing 102628, China)

  • Han Ye

    (School of Information Technology and Network Security, People’s Public Security University of China, Beijing 102628, China)

  • Nan Jia

    (School of Information Technology and Network Security, People’s Public Security University of China, Beijing 102628, China)

Abstract

The chemical terrorist attack is an unconventional form of terrorism with vast scope of influence, strong concealment, high technical means and severe consequences. Chemical terrorism risk refers to the uncertainty of the effects of terrorist organisations using toxic industrial chemicals/drugs and classic chemical weapons to attack the population. There are multiple risk factors infecting chemical terrorism risk, such as the threat degree of terrorist organisations, attraction of targets, city emergency response capabilities, and police defense capabilities. We have constructed a Bayesian network of chemical terrorist attacks to conduct risk analysis. The scenario analysis and sensitivity analysis are applied to validate the model and analyse the impact of the vital factor on the risk of chemical terrorist attacks. The results show that the model can be used for simulation and risk analysis of chemical terrorist attacks. In terms of controlling the risk of chemical terrorist attack, patrol and surveillance are less critical than security checks and police investigations. Security check is the most effective approach to decrease the probability of successful attacks. Different terrorist organisations have different degrees of threat, but the impacts of which are limited to the success of the attack. Weapon types and doses are sensitive to casualties, but it is the level of emergency response capabilities that dominates the changes in casualties. Due to the limited number of defensive resources, to get the best consequence, the priority of the deployment of defensive sources should be firstly given to governmental buildings, followed by commercial areas. These findings may provide the theoretical basis and method support for the combat of the public security department and the safety prevention decision of the risk management department.

Suggested Citation

  • Rongchen Zhu & Xiaofeng Hu & Xin Li & Han Ye & Nan Jia, 2020. "Modeling and Risk Analysis of Chemical Terrorist Attacks: A Bayesian Network Method," IJERPH, MDPI, vol. 17(6), pages 1-23, March.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:6:p:2051-:d:334625
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    References listed on IDEAS

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    Cited by:

    1. Yunmeng Lu & Tiantian Wang & Tiezhong Liu, 2020. "Bayesian Network-Based Risk Analysis of Chemical Plant Explosion Accidents," IJERPH, MDPI, vol. 17(15), pages 1-20, July.
    2. Yoshiaki Nomura & Ryoko Otsuka & Wit Yee Wint & Ayako Okada & Ryo Hasegawa & Nobuhiro Hanada, 2020. "Tooth-Level Analysis of Dental Caries in Primary Dentition in Myanmar Children," IJERPH, MDPI, vol. 17(20), pages 1-13, October.

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