Work

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

Year: 2024

Type: article

Abstract: 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.

Source: Ain Shams Engineering Journal

DOI: 10.1016/j.asej.2024.103135

Authors: Mu Chen, Yong Li, Nige Li, Yinan Zhong, Guangxin Guo

Institutions: State Grid Corporation of China (China), Xiamen University, Zhejiang University

Language: English

Topic: Smart Grid Security and Resilience

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Affordable and clean energy

Open Access status: gold

Estimated APC paid: $860