A study of insider threat in nuclear security analysis using game theoretic modeling

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An Insider poses a greater threat to the security system of a nuclear power plant (NPP) because of their ability to take advantage of their access rights and knowledge of a facility, to bypass dedicated security measures. If an insider colludes with an external terrorist group, this poses a key threat to the safety security interface. However, despite the importance of the insider threat, few studies have been conducted to quantitatively analyze an insider threat. This research examines the quantitative framework for investigating the implications of insider threat, taking a novel approach. Conventional tools assessing the security threats to nuclear facilities focus on a limited number of attack pathways. These are defined by the modeler and are based On simple probabilistic calculations. They do not capture the adversary's intentions nor do they account for their response and adaptation to defensive investments. As an alternative way of performing physical protection analysis, this research explores the use of game theoretic modeling of Physical Protection Systems (PPS) analysis by incorporating the implications of an insider threat, to address the issues of intentionality and interactions. The game theoretic approach has the advantage of modeling an intelligent adversary and insider who has an intention to do harm and complete knowledge of the facility. Through a quantitative assessment and sensitivity analysis, vulnerable but important parameters in this model were identified. This made it possible to determine which insider threat is more important. The results of this analysis can be used to prioritize the implementation of PPS improvements in a nuclear facility. In addition, the results from this analytic framework can be a valuable reference tool in the process of policy making in the nuclear security field. (C) 2017 Elsevier Ltd. All rights reserved.
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ANNALS OF NUCLEAR ENERGY, v.108, pp.301 - 309

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NE-Journal Papers(저널논문)
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