基于机器学习的网络流量识别方法研究  

Research on Network Traffic Recognition Based on Machine Learning

作　　者：孙裕康 SUN Yukang(School of Mathematics and Information,South China Agricultural University,Guangzhou Guangdong 510000,China)

机构地区：[1]华南农业大学数学与信息学院,广东广州510000

出　　处：《信息与电脑》2020年第23期53-55,共3页Information & Computer

摘　　要：本文主要探究基于机器学习的网络流量识别方法,首先以网络流量识别方法为切入点,分析SVM算法与AdaBoost算法结合应用,进而提出了算法改进措施及算法流程,最后以此为研究基础进行实验分析。实验结果表明,该算法对于各类文件数据的准确率及反馈率均能满足网络流量识别需求。This paper mainly explores the network traffic identification method based on machine learning.Firstly,taking the network traffic identification method as the breakthrough point,it analyzes the application of SVM algorithm combined with AdaBoost algorithm,and then puts forward the improvement measures and algorithm process.Finally,it carries out the experimental analysis on the basis of this research.Experimental results show that the accuracy and feedback rate of the algorithm can meet the needs of network traffic identification.

关 键 词：机器学习 网络流量识别 识别方法 

分 类 号：TP393.06[自动化与计算机技术—计算机应用技术] TP181[自动化与计算机技术—计算机科学与技术]