李刚, 杨涛, 陈怡潇, 辛锐, 申培培, 余锦河. 基于软件定义的变电站安全风险评估方法研究[J]. 电力信息与通信技术, 2022, 20(8): 83-90. DOI: 10.16543/j.2095-641x.electric.power.ict.2022.08.009
引用本文: 李刚, 杨涛, 陈怡潇, 辛锐, 申培培, 余锦河. 基于软件定义的变电站安全风险评估方法研究[J]. 电力信息与通信技术, 2022, 20(8): 83-90. DOI: 10.16543/j.2095-641x.electric.power.ict.2022.08.009
LI Gang, YANG Tao, CHEN Yixiao, XIN Rui, SHEN Peipei, YU Jinhe. Research on the Risk Assessment Method of Substation Security Based on Software Defined Network[J]. Electric Power Information and Communication Technology, 2022, 20(8): 83-90. DOI: 10.16543/j.2095-641x.electric.power.ict.2022.08.009
Citation: LI Gang, YANG Tao, CHEN Yixiao, XIN Rui, SHEN Peipei, YU Jinhe. Research on the Risk Assessment Method of Substation Security Based on Software Defined Network[J]. Electric Power Information and Communication Technology, 2022, 20(8): 83-90. DOI: 10.16543/j.2095-641x.electric.power.ict.2022.08.009

基于软件定义的变电站安全风险评估方法研究

Research on the Risk Assessment Method of Substation Security Based on Software Defined Network

  • 摘要: 电力系统信息化程度的加深及网络规模的扩大使变电站风险评估工作的难度增加,网络传输过程中暴露的问题也日益增加。如何针对变电站中存在的安全问题进行定量化的评估工作,是目前面临的一个挑战。在此背景下,文章通过结合软件定义网络(software defined network,SDN)数控分离的特性,构造出集中控制、流量管控下的软件定义变电站架构;其次,提出改进的攻击图风险评估方法,引入灵敏度概念实现定量评估。实验结果证实该方法能较好地实现对软件定义变电站的安全风险定量评估。

     

    Abstract: In the power system, the deepening of the information level and the expansion of the network scale make the risk assessment work of the substation more difficult, and the problems exposed in the network transmission process are also increasing. How to quantitatively evaluate the safety problems in substations is a challenge. In this context, this paper combines the characteristics of software-defined network (Software Defined Network, SDN) data and control separation to construct a software-defined substation architecture under centralized control and flow control. Secondly, an improved attack graph risk assessment method is proposed, and the concept of sensitivity is introduced to realize quantitative evaluation. The experimental results show that the method can better realize the quantitative assessment of the safety risk of the software-defined substation.

     

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