摘要
为降低智能电网的安全风险值评估误差,引入大数据技术设计一种新的安全态势感知算法。通过模糊聚类法对信息进行分析,建立网络安全态势感知架构,通过平台部署架构提出主动防御模型思想。列出模糊矩阵,表达数据间的相似性关系,根据神经网络模型输出后的数据信息,构建学习模型,实现网络信息传输安全态势的感知。实验结果表明,设计算法能够有效提高安全风险值评估能力,降低评估误差。
In order to reduce the evaluation error of smart grid security risk value,a new security situation awareness algorithm is designed by introducing big data technology.The information is analyzed by fuzzy clustering method,the network security situation awareness architecture is established,and the idea of active defense model is proposed through platform deployment architecture.The fuzzy matrix is listed to express the similarity relationship between the data.According to the data information output by the neural network model,the learning model is constructed to realize the security situation awareness of network information transmission.The experimental results show that the design algorithm can effectively improve the ability of safety risk evaluation and reduce the evaluation error.
作者
张国萍
ZHANG Guoping(Guangzhou Huashang Vocational College,Guangzhou 511300,China)
出处
《电子设计工程》
2022年第12期185-188,193,共5页
Electronic Design Engineering
基金
广东省普通高校特色创新项目(2019GKTSCX168)。
关键词
大数据
网络信息
传输安全
态势感知算法
big data
network information
transmission security
situation awareness algorithm