Exploiting Contactless Side Channels in Wireless Charging Power Banks for User Privacy Inference via Few-shot Learning
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Title of host publication | ACM MobiCom '23 |
Subtitle of host publication | Proceedings of the 29th Annual International Conference on Mobile Computing and Networking |
Publisher | Association for Computing Machinery |
Pages | 1105-1119 |
Number of pages | 15 |
ISBN (print) | 978-1-4503-9990-6 |
Publication status | Published - Oct 2023 |
Conference
Title | 29th Annual International Conference on Mobile Computing and Networking, MobiCom 2023 |
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Location | Riu Plaza España Hotel |
Place | Spain |
City | Madrid |
Period | 2 - 6 October 2023 |
Link(s)
Abstract
Recently, power banks for smartphones have begun to support wireless charging. Although these wireless charging power banks appear to be immune to most reported vulnerabilities in either power banks or wireless charging, we have found a new contactless wireless charging side channel in these power banks that leaks user privacy from their wireless charging smartphones without compromising either power banks or victim smartphones. We have proposed BankSnoop to demonstrate the practicality of our newly discovered wireless charging side channel in power banks. Specifically, it leverages the coil whine and magnetic field disturbance emitted by a power bank when wirelessly charging a smartphone and adopts the few-shot learning to recognize the app running on the smartphone and uncover keystrokes. We evaluate the effectiveness of BankSnoop using commodity wireless charging power banks and smartphones, and the results show it achieves over 90% accuracy on average in recognizing app launching and keystrokes. It also presents high adaptability when coming to different smartphone models, power banks, etc., achieving over 85% accuracy with 10-shot learning.
© 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.
© 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.
Research Area(s)
- Wireless charging power bank, Contactless side channel, Few-shot learning
Bibliographic Note
Research Unit(s) information for this publication is provided by the author(s) concerned.
Citation Format(s)
Exploiting Contactless Side Channels in Wireless Charging Power Banks for User Privacy Inference via Few-shot Learning. / Ni, Tao; Li, Jianfeng; Zhang, Xiaokuan et al.
ACM MobiCom '23: Proceedings of the 29th Annual International Conference on Mobile Computing and Networking. Association for Computing Machinery, 2023. p. 1105-1119 73.
ACM MobiCom '23: Proceedings of the 29th Annual International Conference on Mobile Computing and Networking. Association for Computing Machinery, 2023. p. 1105-1119 73.
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review