TY - GEN
T1 - Non-cooperative wi-fi localization and its privacy implications
AU - Abedi, Ali
AU - Vasisht, Deepak
N1 - We thank anonymous reviewers and our shepherd for providing valuable and insightful feedback on this paper. We acknowledge the support of the Natural Sciences and Engineering Research Council of Canada (NSERC).
PY - 2022/10/14
Y1 - 2022/10/14
N2 - We present Wi-Peep-a new location-revealing privacy attack on non-cooperative Wi-Fi devices. Wi-Peep exploits loopholes in the 802.11 protocol to elicit responses from Wi-Fi devices on a network that we do not have access to. It then uses a novel time-of-flight measurement scheme to locate these devices. Wi-Peep works without any hardware or software modifications on target devices and without requiring access to the physical space that they are deployed in. Therefore, a pedestrian or a drone that carries a Wi-Peep device can estimate the location of every Wi-Fi device in a building. Our Wi-Peep design costs $20 and weighs less than 10 g. We deploy it on a lightweight drone and show that a drone flying over a house can estimate the location of Wi-Fi devices across multiple floors to meter-level accuracy. Finally, we investigate different mitigation techniques to secure future Wi-Fi devices against such attacks.
AB - We present Wi-Peep-a new location-revealing privacy attack on non-cooperative Wi-Fi devices. Wi-Peep exploits loopholes in the 802.11 protocol to elicit responses from Wi-Fi devices on a network that we do not have access to. It then uses a novel time-of-flight measurement scheme to locate these devices. Wi-Peep works without any hardware or software modifications on target devices and without requiring access to the physical space that they are deployed in. Therefore, a pedestrian or a drone that carries a Wi-Peep device can estimate the location of every Wi-Fi device in a building. Our Wi-Peep design costs $20 and weighs less than 10 g. We deploy it on a lightweight drone and show that a drone flying over a house can estimate the location of Wi-Fi devices across multiple floors to meter-level accuracy. Finally, we investigate different mitigation techniques to secure future Wi-Fi devices against such attacks.
UR - http://www.scopus.com/inward/record.url?scp=85140876157&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85140876157&partnerID=8YFLogxK
U2 - 10.1145/3495243.3560530
DO - 10.1145/3495243.3560530
M3 - Conference contribution
AN - SCOPUS:85140876157
T3 - Proceedings of the Annual International Conference on Mobile Computing and Networking, MOBICOM
SP - 570
EP - 582
BT - ACM MobiCom 2022 - Proceedings of the 2022 28th Annual International Conference on Mobile Computing and Networking
PB - Association for Computing Machinery
T2 - 28th ACM Annual International Conference on Mobile Computing and Networking, MobiCom 2022
Y2 - 17 October 2202 through 21 October 2202
ER -