The research of classified method of the network traffic in security access platform based on decision tree

Su Linping, Mu Hongtao, Min Yunlang, Cheng Rui
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引用次数: 4

Abstract

Information security access platform is a core security practices of foundation to construct security access platform system of smart grid, and undertake a various important function of real-time monitoring, security access, secure data transmission and exchange, active defense in all kinds of complex network environments. However, the monitoring of network traffic classification is directly related to the electric power information network in smart grid environment has a far-reaching significance; this page is showing aiming at the problem of instability in traditional traffic classification methods, a traffic classification method based on C4.5 decision tree is proposed, which establishes models on the information gain ratio from the training set. Classifier is tested by attributes on test dataset, as well as network traffic is classified by searching classification models; Experiments show that the overall accuracy of our method achieves more than 93% , and the accuracy signal class is more than 90% on open dataset. So the method is effective for classifying various kinds of traffic.
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基于决策树的安全接入平台网络流量分类方法研究
信息安全接入平台是构建智能电网安全接入平台体系的核心安全实践基础,在各种复杂网络环境中承担着实时监控、安全接入、安全数据传输与交换、主动防御等多种重要功能。然而,网络流量分类的监测直接关系到电力信息网络在智能电网环境下的应用具有深远的意义;针对传统流量分类方法存在的不稳定性问题,提出了一种基于C4.5决策树的流量分类方法,该方法基于训练集的信息增益比建立模型。通过测试数据集上的属性对分类器进行测试,通过搜索分类模型对网络流量进行分类;实验表明,该方法在开放数据集上的总体准确率达到93%以上,信号分类准确率达到90%以上。因此,该方法对各类流量的分类是有效的。
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