Title | A Game-Theoretic Analysis of Cyber Attack-Mitigation in Centralized Feeder Automation System |
Publication Type | Conference Paper |
Year of Publication | 2020 |
Authors | Dai, Q., Shi, L. |
Conference Name | 2020 IEEE Power Energy Society General Meeting (PESGM) |
Keywords | attack resources, Automation, Bayes methods, bayesian attack graph, centralized FA system, centralized feeder automation system, cyber attack-mitigation, cyber security, cyber-attacks, distribution network, distribution networks, Economics, FA, Fault tolerance, Fault tolerant systems, fault-tolerant location, fault-tolerant location technique, game theoretic security, game theory, game-theoretic analysis, Games, generalized reduced gradient algorithm, gradient methods, human factors, intelligent electronic devices, particle swarm optimisation, particle swarm optimization, power engineering computing, power system security, Predictive Metrics, probability, PSO., pubcrawl, Resiliency, Scalability, security of data, security resources, simulation, three-stage game-theoretic framework, two-level zero-sum game model |
Abstract | The intelligent electronic devices widely deployed across the distribution network are inevitably making the feeder automation (FA) system more vulnerable to cyber-attacks, which would lead to disastrous socio-economic impacts. This paper proposes a three-stage game-theoretic framework that the defender allocates limited security resources to minimize the economic impacts on FA system while the attacker deploys limited attack resources to maximize the corresponding impacts. Meanwhile, the probability of successful attack is calculated based on the Bayesian attack graph, and a fault-tolerant location technique for centralized FA system is elaborately considered during analysis. The proposed game-theoretic framework is converted into a two-level zero-sum game model and solved by the particle swarm optimization (PSO) combined with a generalized reduced gradient algorithm. Finally, the proposed model is validated on distribution network for RBTS bus 2. |
DOI | 10.1109/PESGM41954.2020.9281583 |
Citation Key | dai_game-theoretic_2020 |