基于RBF神经网络的电力信息网络安全态势感知

Power Information Network Security Situation Awareness Based on RBF Neural Network

本次研究基于RBF神经网络提出了一套网络安全态势感知算法,在此基础上结合电力系统的数据库模块、人机接口模块和数据采集模块建立网络安全态势感知框架,最后通过Cup99数据集对本文所提出的算法实施了仿真验证。经实验研究发现,基于RBF神经网络的电力信息网络安全态势感知技术对于已知网络攻击的识别准确率可达到90%以上。

This study proposes a network security situation awareness algorithm based on RBF neural network, and combines the algorithm with the database module, human-computer interface module and data acquisition module of power system to establish a network security situation awareness framework. Finally, the algorithm proposed in this paper is verified by simulation with CUP99 data set. The experimental results show that the recognition accuracy of power information network security situation awareness technology based on RBF neural network for known network attacks can reach more than 90%.