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Towards the Detection of GPS Spoofing Attacks against Drones by Analyzing Camera’s Video Stream

A Global Positioning System (GPS) spoofing attack can be launched against any commercial GPS sensor in order to interfere with its navigation capabilities. These sensors are installed in a variety of devices and vehicles (e.g., cars, planes, cell phones, ships, UAVs, and more). In this study, we foc...

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Detalles Bibliográficos
Autores principales: Davidovich, Barak, Nassi, Ben, Elovici, Yuval
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9002890/
https://www.ncbi.nlm.nih.gov/pubmed/35408222
http://dx.doi.org/10.3390/s22072608
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author Davidovich, Barak
Nassi, Ben
Elovici, Yuval
author_facet Davidovich, Barak
Nassi, Ben
Elovici, Yuval
author_sort Davidovich, Barak
collection PubMed
description A Global Positioning System (GPS) spoofing attack can be launched against any commercial GPS sensor in order to interfere with its navigation capabilities. These sensors are installed in a variety of devices and vehicles (e.g., cars, planes, cell phones, ships, UAVs, and more). In this study, we focus on micro UAVs (drones) for several reasons: (1) they are small and inexpensive, (2) they rely on a built-in camera, (3) they use GPS sensors, and (4) it is difficult to add external components to micro UAVs. We propose an innovative method, based on the video stream captured by a drone’s camera, for the real-time detection of GPS spoofing attacks targeting drones. The proposed method collects frames from the video stream and their location (GPS coordinates); by calculating the correlation between each frame, our method can detect GPS spoofing attacks on drones. We first analyze the performance of the suggested method in a controlled environment by conducting experiments on a flight simulator that we developed. Then, we analyze its performance in the real world using a DJI drone. Our method can provide different levels of security against GPS spoofing attacks, depending on the detection interval required; for example, it can provide a high level of security to a drone flying at altitudes of 50–100 m over an urban area at an average speed of 4 km/h in conditions of low ambient light; in this scenario, the proposed method can provide a level of security that detects any GPS spoofing attack in which the spoofed location is a distance of 1–4 m (an average of 2.5 m) from the real location.
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spelling pubmed-90028902022-04-13 Towards the Detection of GPS Spoofing Attacks against Drones by Analyzing Camera’s Video Stream Davidovich, Barak Nassi, Ben Elovici, Yuval Sensors (Basel) Article A Global Positioning System (GPS) spoofing attack can be launched against any commercial GPS sensor in order to interfere with its navigation capabilities. These sensors are installed in a variety of devices and vehicles (e.g., cars, planes, cell phones, ships, UAVs, and more). In this study, we focus on micro UAVs (drones) for several reasons: (1) they are small and inexpensive, (2) they rely on a built-in camera, (3) they use GPS sensors, and (4) it is difficult to add external components to micro UAVs. We propose an innovative method, based on the video stream captured by a drone’s camera, for the real-time detection of GPS spoofing attacks targeting drones. The proposed method collects frames from the video stream and their location (GPS coordinates); by calculating the correlation between each frame, our method can detect GPS spoofing attacks on drones. We first analyze the performance of the suggested method in a controlled environment by conducting experiments on a flight simulator that we developed. Then, we analyze its performance in the real world using a DJI drone. Our method can provide different levels of security against GPS spoofing attacks, depending on the detection interval required; for example, it can provide a high level of security to a drone flying at altitudes of 50–100 m over an urban area at an average speed of 4 km/h in conditions of low ambient light; in this scenario, the proposed method can provide a level of security that detects any GPS spoofing attack in which the spoofed location is a distance of 1–4 m (an average of 2.5 m) from the real location. MDPI 2022-03-29 /pmc/articles/PMC9002890/ /pubmed/35408222 http://dx.doi.org/10.3390/s22072608 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Davidovich, Barak
Nassi, Ben
Elovici, Yuval
Towards the Detection of GPS Spoofing Attacks against Drones by Analyzing Camera’s Video Stream
title Towards the Detection of GPS Spoofing Attacks against Drones by Analyzing Camera’s Video Stream
title_full Towards the Detection of GPS Spoofing Attacks against Drones by Analyzing Camera’s Video Stream
title_fullStr Towards the Detection of GPS Spoofing Attacks against Drones by Analyzing Camera’s Video Stream
title_full_unstemmed Towards the Detection of GPS Spoofing Attacks against Drones by Analyzing Camera’s Video Stream
title_short Towards the Detection of GPS Spoofing Attacks against Drones by Analyzing Camera’s Video Stream
title_sort towards the detection of gps spoofing attacks against drones by analyzing camera’s video stream
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9002890/
https://www.ncbi.nlm.nih.gov/pubmed/35408222
http://dx.doi.org/10.3390/s22072608
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