Huadong Mo, Xun Xiao, Giovanni Sansavini, Daoyi Dong
{"title":"Optimal defense resource allocation against cyber-attacks in distributed generation systems","authors":"Huadong Mo, Xun Xiao, Giovanni Sansavini, Daoyi Dong","doi":"10.1177/1748006x231196259","DOIUrl":null,"url":null,"abstract":"The deployment of advanced information and communication technologies necessitates considering new security threats, such as distributed denial of service attacks and malware, which can fault power generators and feeders and exacerbate power outages in distributed generation systems (DGS). Existing cyber-security studies fail to validate the attacker–defender game model between operators and hackers or provide a DGS model that accounts for realistic characteristics and operations. Furthermore, current game models may be infeasible for large-scale systems and are not robust against uncertainties owing to the use of metaheuristic algorithms. To overcome these gaps, this study quantified the result of a game using the contest success function and estimated the parameters of this function based on real-world evidence: the dataset of cyber crime incidents from Advisen, US. The DGS management was optimized using the power flow model considering the scenario-based uncertainty stemming from cyber-attacks. A three-stage attack+defend–defend–attack framework is proposed to optimize attack–defense resource allocation using the cooperative game and [Formula: see text]-subgradient method. The results for IEEE 4, 13, 34, 123 and 342 test node feeders show that the proposed framework is applicable to large-scale systems and robust to various types of cyber-attacks. The proposed model and algorithms further enhance the DGS performance under uncertainties by protecting the entire grid or only critical nodes according to the defenders’ objectives.","PeriodicalId":51266,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/1748006x231196259","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0
Abstract
The deployment of advanced information and communication technologies necessitates considering new security threats, such as distributed denial of service attacks and malware, which can fault power generators and feeders and exacerbate power outages in distributed generation systems (DGS). Existing cyber-security studies fail to validate the attacker–defender game model between operators and hackers or provide a DGS model that accounts for realistic characteristics and operations. Furthermore, current game models may be infeasible for large-scale systems and are not robust against uncertainties owing to the use of metaheuristic algorithms. To overcome these gaps, this study quantified the result of a game using the contest success function and estimated the parameters of this function based on real-world evidence: the dataset of cyber crime incidents from Advisen, US. The DGS management was optimized using the power flow model considering the scenario-based uncertainty stemming from cyber-attacks. A three-stage attack+defend–defend–attack framework is proposed to optimize attack–defense resource allocation using the cooperative game and [Formula: see text]-subgradient method. The results for IEEE 4, 13, 34, 123 and 342 test node feeders show that the proposed framework is applicable to large-scale systems and robust to various types of cyber-attacks. The proposed model and algorithms further enhance the DGS performance under uncertainties by protecting the entire grid or only critical nodes according to the defenders’ objectives.
期刊介绍:
The Journal of Risk and Reliability is for researchers and practitioners who are involved in the field of risk analysis and reliability engineering. The remit of the Journal covers concepts, theories, principles, approaches, methods and models for the proper understanding, assessment, characterisation and management of the risk and reliability of engineering systems. The journal welcomes papers which are based on mathematical and probabilistic analysis, simulation and/or optimisation, as well as works highlighting conceptual and managerial issues. Papers that provide perspectives on current practices and methods, and how to improve these, are also welcome