@inproceedings{19c49fbd644c454cb3e0f8c6f0848f46,
title = "ReDroId: Remote drone identification based on visual RSA SecurID Tokens",
abstract = "In an 'open skies' era in which drones are flying among us, a new question arises: how can we distinguish between a friend drone (e.g., carrying a pizza delivery) and a foe drone (e.g., carrying a bomb) in areas that allow drone flights if both drones are identical? In this paper, we propose an authentication scheme that can help an authenticatee distinguish between a foe and friend drone. The authentication is implemented by optically modulating an RSA token using flashing lights which are mounted on the drone. Using a video camera, a trained machine learning model recognizes the flashing lights from the drone and converts them to a binary code which is used to authenticate the drone's identity.",
keywords = "Authentication, Drones, Remote Drone Identification",
author = "Ben Nassi and Aviel Levy and Yaron Pirutin and Asaf Shabtai and Ryusuke Masuoka and Yuval Elovici",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2021 ; Conference date: 07-10-2021 Through 08-10-2021",
year = "2021",
month = oct,
day = "7",
doi = "10.1109/ICECCME52200.2021.9591023",
language = "English",
series = "International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2021",
publisher = "Institute of Electrical and Electronics Engineers",
booktitle = "International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2021",
address = "United States",
}