Research on Network Traffic Identification Technology for Big Data Platform

In the information age, the problem about network security has been more and more serious. For the management of network traffic, the relevant network management agencies want to classify and identify various network traffic in order to supervise. However, more and more network traffic exist in the form of encryption, so that some malicious people damage it in virtue of the encrypted nature of the traffic. On the other hand, on account of the large capacity of the network traffic itself, traditional method for the data analysis can't satisfy it. Therefore, it is necessary to import the platform of the big data. In this paper, we known about the differences of encrypted traffic and unencrypted traffic through the deep studying of the encrypted traffic at first. Secondly, we classify and analyze current technology about the recognition of encrypted traffic, and deduce the algorithm based on the information entropy recognition technology. Finally, we conduct the experiment about the encrypted traffic recognition technology in the big data platform, provides feasibility verification for network traffic research on big data platform, and make a prospect for the next step through the analysis of experimental result.