5G traffic identification method and device based on machine learning

The invention discloses a 5G traffic identification method and device based on machine learning. The method comprises the following steps: acquiring to-be-tested pcap format data and to-be-tested IDX format data of to-be-tested traffic data; inputting the to-be-tested IDX format data and the to-be-tested pcap format data into the supervised learning model and the representation learning model respectively to obtain a supervised learning recognition result and a representation learning recognition result; and obtaining a traffic identification result according to the supervised learning identification result and the representation learning identification result. By analyzing the Pcap file, the network traffic can be classified and identified by using the deep learning model, so that the traditional supervised learning is combined with the unsupervised representation learning, and the identification accuracy is improved. 本发明公开一种基于机器学习的5G流量识别方法及装置，包括获取待测流量数据的待测pcap格式数据及待测IDX格式数据；将待测IDX格式数据与待测pcap格式数据分别输入监督学习模型与表