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Impact Assessment of GNSS Spoofing Attacks on INS/GNSS Integrated Navigation System

In the face of emerging Global Navigation Satellite System (GNSS) spoofing attacks, there is a need to give a comprehensive analysis on how the inertial navigation system (INS)/GNSS integrated navigation system responds to different kinds of spoofing attacks. A better understanding of the integrated...

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Detalles Bibliográficos
Autores principales: Liu, Yang, Li, Sihai, Fu, Qiangwen, Liu, Zhenbo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5982992/
https://www.ncbi.nlm.nih.gov/pubmed/29734715
http://dx.doi.org/10.3390/s18051433
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author Liu, Yang
Li, Sihai
Fu, Qiangwen
Liu, Zhenbo
author_facet Liu, Yang
Li, Sihai
Fu, Qiangwen
Liu, Zhenbo
author_sort Liu, Yang
collection PubMed
description In the face of emerging Global Navigation Satellite System (GNSS) spoofing attacks, there is a need to give a comprehensive analysis on how the inertial navigation system (INS)/GNSS integrated navigation system responds to different kinds of spoofing attacks. A better understanding of the integrated navigation system’s behavior with spoofed GNSS measurements gives us valuable clues to develop effective spoofing defenses. This paper focuses on an impact assessment of GNSS spoofing attacks on the integrated navigation system Kalman filter’s error covariance, innovation sequence and inertial sensor bias estimation. A simple and straightforward measurement-level trajectory spoofing simulation framework is presented, serving as the basis for an impact assessment of both unsynchronized and synchronized spoofing attacks. Recommendations are given for spoofing detection and mitigation based on our findings in the impact assessment process.
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spelling pubmed-59829922018-06-05 Impact Assessment of GNSS Spoofing Attacks on INS/GNSS Integrated Navigation System Liu, Yang Li, Sihai Fu, Qiangwen Liu, Zhenbo Sensors (Basel) Article In the face of emerging Global Navigation Satellite System (GNSS) spoofing attacks, there is a need to give a comprehensive analysis on how the inertial navigation system (INS)/GNSS integrated navigation system responds to different kinds of spoofing attacks. A better understanding of the integrated navigation system’s behavior with spoofed GNSS measurements gives us valuable clues to develop effective spoofing defenses. This paper focuses on an impact assessment of GNSS spoofing attacks on the integrated navigation system Kalman filter’s error covariance, innovation sequence and inertial sensor bias estimation. A simple and straightforward measurement-level trajectory spoofing simulation framework is presented, serving as the basis for an impact assessment of both unsynchronized and synchronized spoofing attacks. Recommendations are given for spoofing detection and mitigation based on our findings in the impact assessment process. MDPI 2018-05-04 /pmc/articles/PMC5982992/ /pubmed/29734715 http://dx.doi.org/10.3390/s18051433 Text en © 2018 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Liu, Yang
Li, Sihai
Fu, Qiangwen
Liu, Zhenbo
Impact Assessment of GNSS Spoofing Attacks on INS/GNSS Integrated Navigation System
title Impact Assessment of GNSS Spoofing Attacks on INS/GNSS Integrated Navigation System
title_full Impact Assessment of GNSS Spoofing Attacks on INS/GNSS Integrated Navigation System
title_fullStr Impact Assessment of GNSS Spoofing Attacks on INS/GNSS Integrated Navigation System
title_full_unstemmed Impact Assessment of GNSS Spoofing Attacks on INS/GNSS Integrated Navigation System
title_short Impact Assessment of GNSS Spoofing Attacks on INS/GNSS Integrated Navigation System
title_sort impact assessment of gnss spoofing attacks on ins/gnss integrated navigation system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5982992/
https://www.ncbi.nlm.nih.gov/pubmed/29734715
http://dx.doi.org/10.3390/s18051433
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