From 5G to 6G: It is time to sniff the communications between a base station and core networks

Thanks to mobility and large coverage, 6G mobile networks introduce satellites and unmanned aerial vehicles as aerial base stations (ABS) in the 6G era. Instead of using a wired backhaul in 5G and its predecessor, an ABS leverages a wireless channel to a core network (CN). However, such a wireless channel design introduces new security challenges. In this paper, we present that passive attackers could sniff the ABS-CN wireless channel and identify what users are doing based on deep learning methods. We collect GTP protocol data on our testbed and use convolutional neural networks to classify 5 types of encrypted App traffic, like IG and TikTok. Experiment results proved the effectiveness of the proposed method, revealing the confidential data leakage problem on the 6G wireless ABS-CN channel.