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Indoor location services often use Bluetooth low energy (BLE) devices for their low energy consumption and easy implementation. Applications like device monitoring, ranging, and asset tracking utilize the received signal strength (RSS) of the BLE signal to estimate the proximity of a device from the receiver. However, in multipath environments, RSS-based solutions may not provide an accurate estimation. In such environments, receivers with antenna arrays are used to calculate the difference in time of flight (ToF) and therefore calculate the direction of arrival (DoA) of the Bluetooth signal. Other techniques like triangulation have also been used, such as having multiple transmitters or receivers as a network of sensors. To find a lost item, devices like Tile© use an onboard beeper to notify users of their presence. In this paper, we present a system that uses a single-measurement device and describe the method of measurement to estimate the location of a BLE device using RSS. A BLE device is configured as an Eddystone beacon for periodic transmission of advertising packets with RSS information. We developed a smartphone application to read RSS information from the beacon, designed an algorithm to estimate the DoA, and used the phone’s internal sensors to evaluate the DoA with respect to true north. The proposed measurement method allows for asset tracking by iterative measurements that provide the direction of the beacon and take the user closer at every step. The receiver application is easily deployable on a smartphone, and the algorithm provides direction of the beacon within a 30° range, as suggested by the provided results.
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Track You: A Deep Dive into Safety Alerts for Apple AirTags
Bluetooth-based item trackers have sparked apprehension over their potential misuse in harmful stalking and privacy violations. In response, manufacturers have implemented safety alerts to notify victims of extended tracking by unknown item trackers. In this study, we specifically investigate the anti-stalking mechanism of Apple's AirTag. We identify and analyze potential triggers of safety alerts that have not been examined in previous research, such as the local time, the victim's device model, AirTag's battery life, and the distance between the AirTag and the victim's device. Furthermore, we demonstrate a novel possibility of developing a stealthy cloned AirTag capable of tracking victims directly on the Find My app while circumventing safety alerts on the victim’s device. Our experiments demonstrate that, despite regular updates to the public key and MAC address, our cloned AirTag can provide real-time location updates even with a four months old key, thereby highlighting the challenges in designing a robust anti-stalking framework. Furthermore, we propose practical solutions to mitigate stalking risks from cloned AirTags and enhance the existing anti-stalking safeguards for AirTags. These suggestions seek to provide a foundation for similar Bluetooth-based item trackers to improve their anti-stalking protections while ensuring optimal tracking efficiency. We conducted rigorous experiments to validate our findings, ensuring their accuracy and reliability. Our evaluation highlights that safety alerts take over 8 hours to appear during the day and are more prompt during the night, particularly after 11 pm.
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- Award ID(s):
- 1955227
- PAR ID:
- 10533293
- Publisher / Repository:
- Proceedings on Privacy Enhancing Technologies Symposium 2023
- Date Published:
- Journal Name:
- Proceedings on Privacy Enhancing Technologies
- Volume:
- 2023
- Issue:
- 4
- ISSN:
- 2299-0984
- Page Range / eLocation ID:
- 132 to 148
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.56553/popets-2023-0102
