Abstract
Abstract As a basic work of network security, network traffic recognition plays an important role in network resource management and abnormal network traffic monitoring. At present, network traffic identification has become one of the hottest issues in academic research. In the past research, network traffic analysis was mainly done by Port Matching, Deep Packet Inspection. However, these methods are not perfect, and they are not suitable for today. This paper implements a traffic recognition method based on deep learning and machine learning. Besides, this paper implements unsupervised clustering of traffic. On the UNB ISCX data set, the experimental results are quite good.KeywordsNetwork traffic recognitionDeep learningMachine learningUnsupervised clustering
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