Dangerous attack paths analysis for power networks based on adaptive limited depth search and improved Z-score pruning

Aiming at the problems of low efficiency of attack path search in a large-scale power system, a dangerous attack path search analysis method is proposed, which searches the dangerous attack path in the attack graph of the node threat value quantification to realize the security analysis in the power...

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Main Authors: Mu Chen, Yong Li, Nige Li, Yinan Zhong, Guangxin Guo
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Ain Shams Engineering Journal
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Online Access:http://www.sciencedirect.com/science/article/pii/S2090447924005161
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author Mu Chen
Yong Li
Nige Li
Yinan Zhong
Guangxin Guo
author_facet Mu Chen
Yong Li
Nige Li
Yinan Zhong
Guangxin Guo
author_sort Mu Chen
collection DOAJ
description Aiming at the problems of low efficiency of attack path search in a large-scale power system, a dangerous attack path search analysis method is proposed, which searches the dangerous attack path in the attack graph of the node threat value quantification to realize the security analysis in the power system. Firstly, the search benefit is defined according to the number of dangerous path changes at different depths, and then the search limit depth of each node is determined by the search benefit. Then, the relative comparison method based on improved Z-score is used to prune the node by considering the node’s characteristics and environment. Finally, an adaptive depth-limited breadth-first search is performed to obtain the attack paths. Experiments show that the proposed method can improve the search efficiency and reduce the search of unnecessary nodes while ensuring the accuracy of the search results of the attack path.
format Article
id doaj-art-69dc5f66367546499d35c1957c4a7f95
institution Kabale University
issn 2090-4479
language English
publishDate 2024-12-01
publisher Elsevier
record_format Article
series Ain Shams Engineering Journal
spelling doaj-art-69dc5f66367546499d35c1957c4a7f952024-12-18T08:48:29ZengElsevierAin Shams Engineering Journal2090-44792024-12-011512103135Dangerous attack paths analysis for power networks based on adaptive limited depth search and improved Z-score pruningMu Chen0Yong Li1Nige Li2Yinan Zhong3Guangxin Guo4Department of Informatics and Communication Engineering, Xiamen University, Xiamen 361005, China; State Grid Smart Grid Research Institute C. Ltd., Nanjing 210003, China; State Grid Laboratory of Power cyber-Security Protection and Monitoring Technology, Nanjing 210003, China; Corresponding author at: Department of Informatics and Communication Engineering, Xiamen University, Xiamen 361005, China.State Grid Smart Grid Research Institute C. Ltd., Nanjing 210003, China; State Grid Laboratory of Power cyber-Security Protection and Monitoring Technology, Nanjing 210003, ChinaState Grid Smart Grid Research Institute C. Ltd., Nanjing 210003, China; State Grid Laboratory of Power cyber-Security Protection and Monitoring Technology, Nanjing 210003, ChinaCollege of Electrical Engineering, Zhejiang University, Hangzhou, Zhejiang 310038, ChinaState Grid Beijing Electric Power Research Institute, Beijing 100075, ChinaAiming at the problems of low efficiency of attack path search in a large-scale power system, a dangerous attack path search analysis method is proposed, which searches the dangerous attack path in the attack graph of the node threat value quantification to realize the security analysis in the power system. Firstly, the search benefit is defined according to the number of dangerous path changes at different depths, and then the search limit depth of each node is determined by the search benefit. Then, the relative comparison method based on improved Z-score is used to prune the node by considering the node’s characteristics and environment. Finally, an adaptive depth-limited breadth-first search is performed to obtain the attack paths. Experiments show that the proposed method can improve the search efficiency and reduce the search of unnecessary nodes while ensuring the accuracy of the search results of the attack path.http://www.sciencedirect.com/science/article/pii/S2090447924005161Attack graphSearch algorithmPruningVulnerabilityPower networks
spellingShingle Mu Chen
Yong Li
Nige Li
Yinan Zhong
Guangxin Guo
Dangerous attack paths analysis for power networks based on adaptive limited depth search and improved Z-score pruning
Ain Shams Engineering Journal
Attack graph
Search algorithm
Pruning
Vulnerability
Power networks
title Dangerous attack paths analysis for power networks based on adaptive limited depth search and improved Z-score pruning
title_full Dangerous attack paths analysis for power networks based on adaptive limited depth search and improved Z-score pruning
title_fullStr Dangerous attack paths analysis for power networks based on adaptive limited depth search and improved Z-score pruning
title_full_unstemmed Dangerous attack paths analysis for power networks based on adaptive limited depth search and improved Z-score pruning
title_short Dangerous attack paths analysis for power networks based on adaptive limited depth search and improved Z-score pruning
title_sort dangerous attack paths analysis for power networks based on adaptive limited depth search and improved z score pruning
topic Attack graph
Search algorithm
Pruning
Vulnerability
Power networks
url http://www.sciencedirect.com/science/article/pii/S2090447924005161
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AT yongli dangerousattackpathsanalysisforpowernetworksbasedonadaptivelimiteddepthsearchandimprovedzscorepruning
AT nigeli dangerousattackpathsanalysisforpowernetworksbasedonadaptivelimiteddepthsearchandimprovedzscorepruning
AT yinanzhong dangerousattackpathsanalysisforpowernetworksbasedonadaptivelimiteddepthsearchandimprovedzscorepruning
AT guangxinguo dangerousattackpathsanalysisforpowernetworksbasedonadaptivelimiteddepthsearchandimprovedzscorepruning