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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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. |
format | Online Article Text |
id | pubmed-9002890 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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