Flow identification method based on network flow gravitation cluster

Abstract

The invention relates to a flow identification method based on network flow gravitation cluster. The method comprises a training stage and an identification stage. The training stage comprises the steps of selecting network flow characteristic attributes, and forming flow training sets after normalization processing is conducted on each network flow; selecting isolation flows by a Z fraction, and isolating the flows; conducting iteration classified-learning on each network flow in the training sets by using semi-supervised learning network flow gravitation cluster principles and methods in all non-isolated flow sets; and at last, finishing classification of the isolation flows and forming a flow classification model. The identification stage comprises the steps of forming a network flow sequence to be identified; conducting flow gravitation classification on each network flow to be identified in network flows, mapping each network flow to specific network traffic business types through a flow cluster and finishing identification to the network flows. According to the flow identification method based on the network flow gravitation cluster, unknown and encrypted flows can be identified, and the locally optimal solution problem of cluster identification is solved, and identification accuracy is improved.

Description

technical field [0001] The invention is a traffic identification method based on network flow gravitational clustering, which is mainly used to solve the problems of low efficiency, poor real-time performance, low accuracy and fineness existing in the current network traffic identification method, and belongs to network security management field. [0002] Background technique [0003] One of the current development trends of network security management is to provide differentiated services and provide different quality of service guarantees, and the premise is to correctly and effectively identify various types of business applications in network traffic. Excellent service identification technology can not only greatly improve the ability of network management, but also predict unknown network traffic to a certain extent. Traffic identification can be used in various modules such as network measurement, network management, content audit, public opinion monitoring, and serv...

AI Technical Summary

Problems solved by technology

[0018]Technical problem: the purpose of this invention is to provide a network traffic business type identification method, by optimizing the local optimal solution of the clustering algorithm, mainly to solve the traffic identification accuracy And the granularity is not high, it is difficult to identify unknown traffic and encrypted traffic problems

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