A Review on Cybersecurity Analysis,Attack Detection,and Attack Defense Methods in Cyber-physical Power Systems  被引量:6

在线阅读下载全文

作  者:Dajun Du Minggao Zhu Xue Li Minrui Fei Siqi Bu Lei Wu Kang Li 

机构地区:[1]Shanghai Key Laboratory of Power Station Automation Technology,School of Mechatronics Engineering and Automation,Shanghai University,Shanghai,China [2]Department of Electrical Engineering,The Hong Kong Polytechnic University,Hong Kong,China [3]Department of Electrical and Computer Engineering,Stevens Institute of Technology,Hoboken,NJ 07030,USA [4]School of Electronic and Electrical Engineering,University of Leeds,Leeds LS29JT,UK [5]IEEE

出  处:《Journal of Modern Power Systems and Clean Energy》2023年第3期727-743,共17页现代电力系统与清洁能源学报(英文)

基  金:supported in part by the National Science Foundation of China(No.92067106);111 Project(No.D18003)。

摘  要:Potential malicious cyber-attacks to power systems which are connected to a wide range of stakeholders from the top to tail will impose significant societal risks and challenges.The timely detection and defense are of crucial importance for safe and reliable operation of cyber-physical power systems(CPPSs).This paper presents a comprehensive review of some of the latest attack detection and defense strategies.Firstly,the vulnerabilities brought by some new information and communication technologies(ICTs)are analyzed,and their impacts on the security of CPPSs are discussed.Various malicious cyber-attacks on cyber and physical layers are then analyzed within CPPSs framework,and their features and negative impacts are discussed.Secondly,two current mainstream attack detection methods including state estimation based and machine learning based methods are analyzed,and their benefits and drawbacks are discussed.Moreover,two current mainstream attack defense methods including active defense and passive defense methods are comprehensively discussed.Finally,the trends and challenges in attack detection and defense strategies in CPPSs are provided.

关 键 词:Cyber-physical power systems security threat attack detection attack defense state estimation machine learning 

分 类 号:TM73[电气工程—电力系统及自动化] TP393.08[自动化与计算机技术—计算机应用技术]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象