Unauthorized Amateur UAV Detection Based on WiFi Statistical Fingerprint Analysis

Amateur drones are enjoying great popularity in recent years due to the wide commercial diffusion of small, rather low-cost devices. More and more user-friendly, easy-to-pilot aerial and terrestrial drones are available off the shelf, and people can even remotely pilot them using their smartphones. This situation brings up the problem of keeping unauthorized drones away from private or sensitive areas, where they can represent a personal or public threat. With this motivation, after a survey of the existing solutions, we propose a WiFi-based approach aimed at detecting nearby aerial or terrestrial devices by performing statistical fingerprint analysis on wireless traffic. This novel detection technique, tested in a variety of real-life scenarios, proved able to efficiently detect and identify intruder drones in all the considered experimental setups, making it a promising unmanned aerial vehicle detection approach in the framework of amateur drone surveillance. © 1979-2012 IEEE.

Авторы
Bisio I. 1, 2 , Garibotto C.1 , Lavagetto F.1 , Sciarrone A.1 , Zappatore S.1
Редакторы
-
Издательство
Institute of Electrical and Electronics Engineers Inc.
Номер выпуска
4
Язык
Английский
Страницы
106-111
Статус
Опубликовано
Подразделение
-
Номер
-
Том
56
Год
2018
Организации
  • 1 University of Genoa, Italy
  • 2 Peoples' Friendship University of Russia, Russian Federation
Ключевые слова
Antennas; Drones; Intrusion detection; Palmprint recognition; Wi-Fi; Wireless local area networks (WLAN); Commercial diffusion; Detection techniques; Fingerprint analysis; Low-cost devices; Sensitive area; User friendly; Wireless traffic; Aircraft detection
Дата создания
19.10.2018
Дата изменения
19.10.2018
Постоянная ссылка
https://repository.rudn.ru/ru/records/article/record/6740/