Passive Multi-User Traffic Analysis Based on 5G NR/LTE Physical Layer

Hang Zhang, Dong Wei, Nan Jiang, Meng Zhang, Xiang Meng, Yang Yang, Weiqing Huang

Abstract: Information leakage through wireless channels poses a significant security concern within contemporary cellular networks, such as 5G new radio (NR). Among the myriad of potential attack vectors, passive traffic analysis (PTA) stands out as a pervasive and surreptitious threat, which allows attackers to discern the specific services utilized by unsuspecting victims without their noticing. In this work, we present a pioneering approach to achieve fine-grained service identification by adopting an unexplored perspective: mapping traffic transmission patterns to physical layer time-frequency occupancy patterns, which we refer to as Passive Time-Frequency Traffic (PTTF). Additionally, it selects the uplink control channel that carries the acknowledgment/negative acknowledgment (ACK/NACK) feedback within the Hybrid Automatic Repeat reQuest (HARQ) process as the data source. Statistical features of ACK/NACK time-frequency resources are extracted for traffic classification, and activities are recognized from a three-tier classification algorithm. For validation, we conduct field experiments targeting commercialized smartphones within the real-world operator’s network. This setup effectively mirrors practical scenarios, as the resources within the target frequency band can also be allocated to other equipment in the operator’s network. Furthermore, cross-validation experiments involving different smartphone brands and various network formats are conducted in order to ascertain the generalizability of the proposed PTTF.

External IDs:dblp:journals/tifs/ZhangWJZMYH25