Passive traffic analysis based on resource occupancy of mobile communication uplink control channel

Abstract

Traffic identification is a vital technology in network security. Currently, the identification of mobile network traffic is based on the downlink data in the air interface. This is because it is difficult to synchronize uplinks and obtain uplink traffic data in real-world environments. We propose to utilize mobile communication network sideband resource occupancy for traffic identification. This method captures the uplink IQ data and draws a time-frequency resource map. In order to reduce the computational complexity, we only use the sideband portion of the time-frequency resource map for identification. Based on the different colors reflected on the time-frequency resource map by different users' uplink transmitting power, we distinguish the number of users by color and separate the different user data. The result shows that the accuracy of user number identification is up to 95%. Finally, we use Resnet18 to identify the service of the separated pictures. The F1 parameter of the Resnet18 network reaches 88%.