能源运输系统的社会增强防御

IF 4.5 2区 计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS
Alexis Pengfei Zhao;Shuangqi Li;Yunqi Wang;Mohannad Alhazmi
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引用次数: 0

摘要

信息和通信技术(ICT)基础设施与电动汽车(ev)的普及日益紧密地交织在一起,导致能源网络和交通网络的一致融合。然而,这些系统固有的数据通信和处理能力过剩也对网络安全构成潜在威胁。因此,针对可再生能源渗透的绿色综合电力运输网络(IPTN),提出了分岔物流运营和网络攻击防御策略。这一战略利用电动汽车的社会参与潜力来扩大防御行动。该分支包括一个旨在加强和保持IPTN内部资源分配的排除阶段和一个旨在通过快速响应措施减轻网络攻击有害影响的防御阶段。传统的措施,如减载和操作调整,通过创新的防御参与激励,旨在获得电动汽车用户的额外支持。提出了一种基于Kullback-Leibler散度的平均风险分布鲁棒优化方法,以解决模拟网络攻击后果时数据可用性的局限性。通过城市IPTN的案例研究进行实证调查,以评估网络攻击的不利影响,并研究旨在最大限度地减轻其影响的对策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Socially Enhanced Defense in Energy-Transportation Systems
The ever-increasing entwinement of information and communication technology (ICT) infrastructure with the proliferation of electric vehicles (EVs) has resulted in a congruent coalescence of energy and transportation networks. However, the surfeit of data communication and processing capabilities inherent in these systems also poses a potential peril to cyber security. Hence, a bifurcated logistics operation and cyberattack defense strategy have been propounded for green integrated power-transportation networks (IPTN) with renewable penetration. This strategy leverages the potential of social participation from EVs to amplify the defense operation. The bifurcation comprises of a preclusive stage aimed at fortifying and preserving resource allocation within IPTN and a defensive stage aimed at mitigating the deleterious impacts of cyberattacks through rapid response measures. Conventional measures such as load shedding and operation adjustments are augmented by an innovative defense involvement incentive, designed to elicit additional support from EV users. A mean-risk distributionally robust optimization methodology predicated on Kullback–Leibler divergence is posited to address the limitations in data availability in simulating cyberattack consequences. Empirical investigations through case studies in an urbane IPTN are conducted to evaluate the adverse impacts of cyberattacks and examine countermeasures aimed at mitigating their effects to the greatest extent possible.
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来源期刊
IEEE Transactions on Computational Social Systems
IEEE Transactions on Computational Social Systems Social Sciences-Social Sciences (miscellaneous)
CiteScore
10.00
自引率
20.00%
发文量
316
期刊介绍: IEEE Transactions on Computational Social Systems focuses on such topics as modeling, simulation, analysis and understanding of social systems from the quantitative and/or computational perspective. "Systems" include man-man, man-machine and machine-machine organizations and adversarial situations as well as social media structures and their dynamics. More specifically, the proposed transactions publishes articles on modeling the dynamics of social systems, methodologies for incorporating and representing socio-cultural and behavioral aspects in computational modeling, analysis of social system behavior and structure, and paradigms for social systems modeling and simulation. The journal also features articles on social network dynamics, social intelligence and cognition, social systems design and architectures, socio-cultural modeling and representation, and computational behavior modeling, and their applications.
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