Path analysis attack prediction method for electric power CPS

被引:0
|
作者
Xia Z. [1 ,2 ,3 ]
Li W. [1 ,2 ]
Jiang L. [1 ,2 ]
Xu M. [3 ]
机构
[1] Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation, Changsha University of Science and Technology, Changsha
[2] School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha
[3] School of Computer, National University of Defense Technology, Changsha
关键词
Attack probability graph; Cross-origin attack probability; Cross-origin mean time; Electric CPS security; Path prediction;
D O I
10.16511/j.cnki.qhdxxb.2018.26.012
中图分类号
O212 [数理统计];
学科分类号
摘要
The electric power industry needs to defend against multi-step cross-domain attacks seeking to damage electric power CPS. This paper presents path analysisa electric power CPS attack prediction method that defines a common attack graph based on a probability attack graph model. The Cross-origin attack probability and the cross-origin mean time to compromise are used to quantify the exploit difficulty and the attacker proficiency for offensive and defensive actions to protect the power infrastructure. When attacks are detected in real time, the improved Dijkstra algorithm will enumerate possible follow-up attack paths. The two quantitative indicators are combined to predict the greatest threat attack path. Simulations show that this method can more effectively predict the attack path as a good defensive strategy for electric power CPS security management. © 2018, Tsinghua University Press. All right reserved.
引用
收藏
页码:157 / 163
页数:6
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