摘要
信息技术的快速发展在为人们的日常生活带来便利的同时给网络安全带来较多隐患。为提高现有通信信息安全保护技术的水平,从统计学角度出发,根据多元统计分析、相关性分析以及主成分分析的方法统计和降维网络流量数据,并引入支持向量机(Support Vector Machine,SVM)进行改进,提出一种新型通信信息自动化检测模型。实验结果表明,多元统计相关性降维分析法下的数据统计和降维效果最明显,同时检测模型的准确率最高为92.4%,召回率最高为85.7%,F1值最高为89.1%,误报率最低为8.4%。由此可知,研究所提方法具有一定的可行性和优越性,能够为通信信息安全保护技术提供一种新的方法。
The rapid development of information technology brings convenience to daily life while bringing more hidden dangers to network security.In order to improve the level of existing communication information security protection technology,a new type of automated detection model for communication information is proposed from a statistical point of view,based on the methods of multivariate statistical analysis,correlation analysis and principal component analysis to statistic and dimensionality reduction of network traffic data,and the introduction of the support vector machine for improvement.The experimental results show that the data statistics and dimensionality reduction under the multivariate statistical correlation and dimensionality reduction analysis method have the most obvious effect,while the detection model has the highest accuracy rate of 92.4%,the highest recall rate of 85.7%,the highest F1 value of 89.1%,and the lowest false alarm rate of 8.4%.From this,it can be seen that the proposed method of the study has certain feasibility and superiority,and the study aims to provide a new method for communication information security protection technology.
作者
鲁勇
LU Yong(State Grid Shannan Power Supply Company,Shannan 856000,China)
出处
《通信电源技术》
2024年第5期209-212,共4页
Telecom Power Technology
关键词
统计学
通信信息
自动化检测
网络流量
支持向量机(SVM)
statistics
communication information
automated detection
network traffic
Support Vector Machines(SVM)
