Network traffic classification method, system and device

Abstract

The invention discloses a network traffic classification method. The method comprises the following steps: receiving an input real data set and a to-be-tested data set; performing data processing on the real data set to obtain a training data set; training the preset model by using the training data set to obtain a network traffic classification model; and classifying the to-be-tested data set byusing the network traffic classification model to obtain a classification result. According to the invention, data processing is carried out on the received real data set; according to the technical scheme, the training data set is acquired through the network traffic classification model, so that the training data set has all characteristics of the real data set, the network traffic classification model trained by using the training data set can classify the to-be-tested data set according to the characteristics of the real data, the acquired classification result is more accurate, and the network traffic identification precision is improved. The invention also provides a network traffic classification system and device, and a computer readable storage medium, which have the above beneficial effects.

Description

Technical field [0001] This application relates to the field of network traffic classification, and in particular to a method, system, device and computer-readable storage medium for network traffic classification. Background technique [0002] In the past ten years, with the development of the network, the integration of mobile networks and the Internet has intensified, and the competition between network management services and web services has intensified. The increasingly rich data services used by users have intensified the challenge of effective network management. Sex. The network bandwidth is consumed and the network becomes congested, which greatly reduces the performance of the network, resulting in poor user experience, degradation of the Quality of Experience (QoE) model, and endless problems of the Quality of Service (QoS) model. The constantly changing characteristics of Internet traffic pose challenges to the reliability of traditional methods. Effective network ...

AI Technical Summary

Problems solved by technology

The network bandwidth is consumed, the network becomes congested, and the performance of the network is greatly reduced, resulting in poor user experience, degradation of the Quality of Experience (QoE) model, and endless problems in the Quality of Service (QoS) model

Changing Internet traffic characteristics challenge the reliability of traditional methods

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