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Study on Resource Optimal Allocation of Internal Threat Nuclear Security Events Based on Stackelberg Game

Published: 03 August 2024 Publication History

Abstract

Insider threats are a key issue in the physical protection of nuclear materials and facilities. In order to study the influence of insiders, the Stackelberg game is introduced into the internal threat nuclear security events, considering the defensive resource budget of physical protection system upgrade, and using mixed integer programming, the Stackelberg game scenario between external adversaries and defenders is mathemically described. Then, combined with the undetected probability, travel time and other main input parameters, the built-in accurate algorithm of CPLEX and YALMIP and MATLAB software is used to solve the model, and the interaction between the intention and strategy of the game participants is realized. The results show that compared with passive insiders, insiders with higher access rights and in the main path have a greater impact on game equilibrium. Finally, it provides some reasonable recommendations for optimizing the allocation of internal threat nuclear security event resources from the improvement strategy of physical protection system.

References

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  1. Study on Resource Optimal Allocation of Internal Threat Nuclear Security Events Based on Stackelberg Game

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    ASENS '24: Proceedings of the International Conference on Algorithms, Software Engineering, and Network Security
    April 2024
    759 pages
    ISBN:9798400709784
    DOI:10.1145/3677182
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 03 August 2024

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