Research on Network Traffic Classification Based on Machine Learning
With the rapid development of the Internet,network traffic is growing rapidly in quantity and com-plexity.How to quickly and accurately identify the type of network traffic has become a hot spot in the field of com-puter networks.Traffic classification is the foundation of network traffic management,and its purpose is to identify and classify different types of traffic.Currently,traffic classification based on machine learning is a very promising technique.Machine learning algorithms can learn features from large amounts of data and apply them to network traffic,which can improve the accuracy of classification and help network managers provide people with a better on-line experience.This article first introduces the basic concepts of network traffic classification and traditional net-work traffic classification methods,and then introduces two network traffic algorithms based on machine learning.
NETL
NSTL
万方数据
维普
