Encrypted traffic classification method based on twin neural network

Abstract

The invention belongs to the technical field of network encrypted traffic classification, and particularly relates to an encrypted traffic classification method based on a twin neural network. The method comprises the following steps: firstly, extracting packet features of data packets in to-be-classified network flow data, and carrying out feature cascading to obtain packet feature vectors; inputting the packet feature vector into a trained feature processing network model, and sequentially performing deep feature mining, flattening processing and feature compression on the packet feature vector to obtain a flow vector; and finally, comparing the output vector of the to-be-classified network flow data with the output vectors of the network flow data of various known categories so as to classify the to-be-classified network flow data. The feature processing network model used in the method is simple in structure, a multi-head attention mechanism is adopted to capture the relationship between data packets and improve the parallelization degree, a simple one-dimensional CNN is used for further feature extraction and fusion, and a part of the network structure is repeatedly used to reduce the parameter quantity, so that the algorithm is more efficient. Therefore, simple and efficient unknown traffic discovery and classification are realized.

Description

technical field [0001] The invention belongs to the technical field of network encrypted traffic classification, and in particular relates to a twin neural network-based encrypted traffic classification method. Background technique [0002] With the rapid development of the Internet, network applications and protocols emerge in an endless stream, which makes the types of network traffic more complex and numerous, and poses certain obstacles to network traffic management. At the same time, data leakage, network infiltration, identity theft, and ransomware incidents occur frequently. Countries continue to promulgate new regulations and norms on network security. Users' needs for security and privacy are becoming increasingly urgent. The overall network traffic is showing a trend towards encryption. trend. Network traffic identification refers to classifying network traffic into different sets by observing the characteristics of network traffic according to specific goals. It ...

AI Technical Summary

Problems solved by technology

[0006] The present invention provides a method for classifying encrypted traffic based on a twin neural network, which is used to solve the problem of being unable to adapt to complex and changeable network environments due to the complex model structure in the prior art

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