Research on Satellite Traffic Classification Based on Deep Packet Recognition and Convolution Neural Network.

Over the past decade, Satellite communication has been a crucial topic. In particular, as we move from the 5G era to the 6G era, satellites will play an increasingly critical role in providing coverage and flexibility. With the increasing complexity of satellite network environment, the resource allocation of satellite network is becoming more and more important. Accurate identification of traffic types for classification can allocate network resources more effectively. Each method has its own advantages and disadvantages. In order to minimize the impact of the disadvantages, a reasonable combination of them is a new way to accomplish this task. In this paper, we propose a traffic classification method based on deep packet inspection (DPI) and convolution neural network (CNN), and verify it with open data sets. Experimental results show the effectiveness of our proposed method.