Network traffic data enhancement method and device based on generative confrontation network

Abstract

The embodiment of the present invention provides a method and device for enhancing network flow data based on a generative adversarial net. The method comprises the following steps: acquiring a data set of real network flow in a target scene; training the generative adversarial net model according to the data set; and obtaining final enhanced flow data based on the trained generative adversarial net model. The embodiment of the present invention can be applied to various scenes without the need of expert experience in flow data aspect, flow data enhancement is adaptively implemented, the dataset of the network flow is expanded, and the effect of optimizing network performance by using a machine learning method is improved.

Description

technical field [0001] Embodiments of the present invention belong to the technical field of communication networks, and more specifically, relate to a network traffic data enhancement method and device based on a generative adversarial network. Background technique [0002] In recent years, machine learning (ML) using network traffic data as a training set has been widely used in traffic classification, traffic anomaly detection and network performance optimization. In order to improve the effect of machine learning, a large amount of network traffic data is required. [0003] However, it is difficult to collect effective network traffic data in reality, and the lack of traffic data affects the application effect of machine learning. Therefore, traffic data needs to be synthesized using reasonable and effective network traffic data augmentation methods. In the context of the current communication network, a large number of different types of services have caused the diver...

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the problem of poor universality of the existing network traffic data synthesis method and the lack of authenticity of the synthesized traffic data or at least partially solve the above problems, an embodiment of the present invention provides a network traffic data enhancement method based on a generative confrontation network and device

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