Matthan: Drone Presence Detection by Identifying Physical Signatures in the Drone's RF Communication. Nguyen, P., Truong, H., Ravindranathan, M., Nguyen, A., Han, R., & Vu, T. In Proceedings of the Annual International Conference on Mobile Systems, Applications, and Services (MobiSys), pages 211-224, 6, 2017. ACM.
Matthan: Drone Presence Detection by Identifying Physical Signatures in the Drone's RF Communication [link]Website  abstract   bibtex   
Drones are increasingly flying in sensitive airspace where their presence may cause harm, such as near airports, forest fires, large crowded events, secure buildings, and even jails. This problem is likely to expand given the rapid proliferation of drones for commerce, monitoring, recreation, and other applications. A cost-effective detection system is needed to warn of the presence of drones in such cases. In this paper, we explore the feasibility of inexpensive RF-based detection of the presence of drones. We examine whether physical characteristics of the drone, such as body vibration and body shifting, can be detected in the wireless signal transmitted by drones during communication. We consider whether the received drone signals are uniquely differentiated from other mobile wireless phenomena such as cars equipped with Wi- Fi or humans carrying a mobile phone. The sensitivity of detection at distances of hundreds of meters as well as the accuracy of the overall detection system are evaluated using software defined radio (SDR) implementation.
@inProceedings{
 title = {Matthan: Drone Presence Detection by Identifying Physical Signatures in the Drone's RF Communication},
 type = {inProceedings},
 year = {2017},
 identifiers = {[object Object]},
 keywords = {drone,iot,iotsec,mobile,radio,rf,sdr,security},
 pages = {211-224},
 websites = {http://dx.doi.org/10.1145/3081333.3081354},
 month = {6},
 publisher = {ACM},
 id = {208792fd-2cb0-3322-bd9a-0faf05018595},
 created = {2018-07-12T21:31:33.817Z},
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 citation_key = {nguyen:drone},
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 abstract = {Drones are increasingly flying in sensitive airspace where their presence may cause harm, such as near airports, forest fires, large crowded events, secure buildings, and even jails. This problem is likely to expand given the rapid proliferation of drones for commerce, monitoring, recreation, and other applications. A cost-effective detection system is needed to warn of the presence of drones in such cases. In this paper, we explore the feasibility of inexpensive RF-based detection of the presence of drones. We examine whether physical characteristics of the drone, such as body vibration and body shifting, can be detected in the wireless signal transmitted by drones during communication. We consider whether the received drone signals are uniquely differentiated from other mobile wireless phenomena such as cars equipped with Wi- Fi or humans carrying a mobile phone. The sensitivity of detection at distances of hundreds of meters as well as the accuracy of the overall detection system are evaluated using software defined radio (SDR) implementation.},
 bibtype = {inProceedings},
 author = {Nguyen, Phuc and Truong, Hoang and Ravindranathan, Mahesh and Nguyen, Anh and Han, Richard and Vu, Tam},
 booktitle = {Proceedings of the Annual International Conference on Mobile Systems, Applications, and Services (MobiSys)}
}
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