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 WorksRGC 32 - Refereed conference paper (with host publication)peer-review

9 Scopus Citations
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Author(s)

  • Jianfeng Li
  • Xiaokuan Zhang
  • Chaoshun Zuo
  • Wubing Wang
  • Xiapu Luo

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationACM MobiCom '23
Subtitle of host publicationProceedings of the 29th Annual International Conference on Mobile Computing and Networking
PublisherAssociation for Computing Machinery
Pages1105-1119
Number of pages15
ISBN (print)978-1-4503-9990-6
Publication statusPublished - Oct 2023

Conference

Title29th Annual International Conference on Mobile Computing and Networking, MobiCom 2023
LocationRiu Plaza España Hotel
PlaceSpain
CityMadrid
Period2 - 6 October 2023

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.

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.

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review