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

Tools

Xiong, Ruoting, Tong, Kit-Lun, Ren, Yi ORCID: https://orcid.org/0000-0001-7423-6719, Ren, Wei and Parr, Gerard ORCID: https://orcid.org/0000-0002-9365-9132 (2023) From 5G to 6G: It is time to sniff the communications between a base station and core networks. In: ACM MobiCom '23. Proceedings of the Annual International Conference on Mobile Computing and Networking, MOBICOM . Association for Computing Machinery (ACM), pp. 1478-1479.

Preview

PDF (3570361.3614085) - Published Version
Download (464kB) | Preview

Abstract

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.

Item Type:	Book Section
Uncontrolled Keywords:	6g,deep learning,encrypted data analysis,sniffing attack,wireless channel,computer networks and communications,hardware and architecture,software ,/dk/atira/pure/subjectarea/asjc/1700/1705
Faculty \ School:	Faculty of Science Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Data Science and AI
Related URLs:	http://www.scopus.com/inward/record.url?... https://dl.acm.org/doi/10.1145/3570361.3...
Depositing User:	LivePure Connector
Date Deposited:	13 Nov 2023 18:10
Last Modified:	25 Dec 2024 00:39
URI:	https://ueaeprints.uea.ac.uk/id/eprint/93631
DOI:	10.1145/3570361.3614085

Downloads

Downloads per month over past year

Actions (login required)

View Item