@inproceedings{a6511098748745d281f822bd77b0c79d,
title = "Unauthorized Drone Detection: Experiments and Prototypes",
abstract = "The increase in the number of unmanned aerial vehicles a.k.a. drones pose several threats to public privacy, critical infrastructure and cyber security. Hence, detecting unauthorized drones is a significant problem which received attention in the last few years. In this paper, we present our experimental work on three drone detection methods (i.e., acoustic detection, radio frequency (RF) detection, and visual detection) to evaluate their efficacy in both indoor and outdoor environments. Owing to the limitations of these schemes, we present a novel encryption-based drone detection scheme that uses a two-stage verification of the drone's received signal strength indicator (RSSI) and the encryption key generated from the drone's position coordinates to reliably detect an unauthorized drone in the presence of authorized drones.",
keywords = "Acoustic, drone detection, radar, radio frequency, visual",
author = "Khan, \{Muhammad Asif\} and Hamid Menouar and Khalid, \{Osama Muhammad\} and Adnan Abu-Dayya",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Conference on Industrial Technology, ICIT 2022 ; Conference date: 22-08-2022 Through 25-08-2022",
year = "2022",
month = aug,
day = "25",
doi = "10.1109/ICIT48603.2022.10002815",
language = "English",
series = "Proceedings of the IEEE International Conference on Industrial Technology",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2022 IEEE International Conference on Industrial Technology, ICIT 2022",
address = "United States",
}