Cybersecurity is the security cornerstone of digital transformation of the
power grid and construction of new power systems. The traditional network
security situation quantification method only analyzes from the perspective of
network performance, ignoring the impact of various power application services
on the security situation, so the quantification results cannot fully reflect
the power information network risk state. This study proposes a method for
quantifying security situation of the power information network based on the
evolutionary neural network. First, the security posture system architecture is
designed by analyzing the business characteristics of power information network
applications. Second, combining the importance of power application business,
the spatial element index system of coupled interconnection is established from
three dimensions of network reliability, threat, and vulnerability. Then, the
BP neural network optimized by the genetic evolutionary algorithm is
incorporated into the element index calculation process, and the quantitative
model of security posture of the power information network based on the
evolutionary neural network is constructed. Finally, a simulation experiment
environment is built according to a power sector network topology, and the
effectiveness and robustness of the method proposed in the study are verified.

本文提出了一种基于进化神经网络的电力信息网络安全态势量化方法，根据电力信息网络应用的业务特征分析设计了安全态势系统架构，从网络可靠性、威胁、脆弱性三个维度建立耦合互联的空间元素指标体系，通过遗传进化算法优化的 BP 神经网络，构建了基于进化神经网络的电力信息网络安全态势量化模型，并通过仿真实验验证了该方法的有效性和鲁棒性。