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

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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. Association for Computing Machinery (ACM), pp. 1-2.

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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
Faculty \ School: Faculty of Science
Faculty of Science > School of Computing Sciences
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 13 Nov 2023 18:10
Last Modified: 13 Nov 2023 18:10
URI: https://ueaeprints.uea.ac.uk/id/eprint/93631
DOI: 10.1145/3570361.3614085

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