Abstract
Recent years have witnessed the increasing penetration of wireless charging base stations in the workplace and public areas, such as airports and cafeteria. Such an emerging wireless charging infrastructure has presented opportunities for new indoor localization and identification services for mobile users. In this paper, we present QID, the first system that can identify a Qi-compliant mobile device during wireless charging in real-time. QID extracts features from the clock oscillator and control scheme of the power receiver and employs light-weight algorithms to classify the device. QID adopts 2-dimensional motion unit to emulate a variety of multi-coil designs of Qi, which allows for fine-grained device fingerprinting. Our results show that QID achieves high recognition accuracy. With the prevalence of public wireless charging stations, our results also have important implications for mobile user privacy.
| Original language | English |
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| Title of host publication | Proceedings - 5th ACM/IEEE Conference on Internet of Things Design and Implementation, IoTDI 2020 |
| Publisher | IEEE |
| Pages | 1-13 |
| ISBN (Electronic) | 78-1-7281-6602-5 |
| ISBN (Print) | 978-1-7281-6603-2 |
| DOIs | |
| Publication status | Published - 2020 |
| Externally published | Yes |
| Event | 5th ACM/IEEE Conference on Internet of Things Design and Implementation, IoTDI 2020 - Virtual, Sydney, Australia Duration: 21 Apr 2020 → 24 Apr 2020 https://conferences.computer.org/iotDI/2020/ |
Publication series
| Name | Proceedings - ACM/IEEE Conference on Internet of Things Design and Implementation, IoTDI |
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Conference
| Conference | 5th ACM/IEEE Conference on Internet of Things Design and Implementation, IoTDI 2020 |
|---|---|
| Country/Territory | Australia |
| City | Sydney |
| Period | 21/04/20 → 24/04/20 |
| Internet address |
Research Keywords
- Device recognition
- Qi wireless charging
- Real time processing
