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GNSS spoofing detection using a maximum likelihood-based sliding window method
The Global Navigation Satellite System is vulnerable to interference signals that can potentially disable the system, because the signal strength tends to be very weak. Interference such as jamming, which disables the receiver via excessively high signal strength in the satellite navigation frequenc...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Public Library of Science
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7454987/ https://www.ncbi.nlm.nih.gov/pubmed/32857756 http://dx.doi.org/10.1371/journal.pone.0237146 |
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author | Jeong, Seongkyun |
author_facet | Jeong, Seongkyun |
author_sort | Jeong, Seongkyun |
collection | PubMed |
description | The Global Navigation Satellite System is vulnerable to interference signals that can potentially disable the system, because the signal strength tends to be very weak. Interference such as jamming, which disables the receiver via excessively high signal strength in the satellite navigation frequency band, and spoofing, which induces the receiver to output erroneous position and time data via signals similar to actual navigation signals, disrupt satellite navigation systems. As the threat of interference is increasing, considerable research effort has been expended in an attempt to deal with it in various ways. Spoofing attacks are especially difficult to detect. This paper deals with a technique to detect a spoofing signal and to mitigate attacks on satellite navigation systems. The satellite navigation signal is influenced by the navigation satellite itself and errors due to environmental factors, and spoofing signal detection should be well reflected in the navigation signal. Especially, in the case of mobile receivers, it is not easy to detect a spoofing signal because the exact position of the receiver cannot be known. To detect a spoofing signal, additional hardware may be required; in some cases, heterogeneous sensors, such as inertial sensors, may be used. The technique introduced in this paper effectively discriminates spoofing signals based only on receiver measurements, without the need for additional devices. It generates test statistics based on the pseudorange, which is the measured value of the receiver position, and detects spoofing signals by setting the monitoring interval according to a “sliding window”. Because the proposed method uses output data and measurements obtained from the receiver, it can be applied to general receivers at low cost. |
format | Online Article Text |
id | pubmed-7454987 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-74549872020-09-02 GNSS spoofing detection using a maximum likelihood-based sliding window method Jeong, Seongkyun PLoS One Research Article The Global Navigation Satellite System is vulnerable to interference signals that can potentially disable the system, because the signal strength tends to be very weak. Interference such as jamming, which disables the receiver via excessively high signal strength in the satellite navigation frequency band, and spoofing, which induces the receiver to output erroneous position and time data via signals similar to actual navigation signals, disrupt satellite navigation systems. As the threat of interference is increasing, considerable research effort has been expended in an attempt to deal with it in various ways. Spoofing attacks are especially difficult to detect. This paper deals with a technique to detect a spoofing signal and to mitigate attacks on satellite navigation systems. The satellite navigation signal is influenced by the navigation satellite itself and errors due to environmental factors, and spoofing signal detection should be well reflected in the navigation signal. Especially, in the case of mobile receivers, it is not easy to detect a spoofing signal because the exact position of the receiver cannot be known. To detect a spoofing signal, additional hardware may be required; in some cases, heterogeneous sensors, such as inertial sensors, may be used. The technique introduced in this paper effectively discriminates spoofing signals based only on receiver measurements, without the need for additional devices. It generates test statistics based on the pseudorange, which is the measured value of the receiver position, and detects spoofing signals by setting the monitoring interval according to a “sliding window”. Because the proposed method uses output data and measurements obtained from the receiver, it can be applied to general receivers at low cost. Public Library of Science 2020-08-28 /pmc/articles/PMC7454987/ /pubmed/32857756 http://dx.doi.org/10.1371/journal.pone.0237146 Text en © 2020 Seongkyun Jeong http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Jeong, Seongkyun GNSS spoofing detection using a maximum likelihood-based sliding window method |
title | GNSS spoofing detection using a maximum likelihood-based sliding window method |
title_full | GNSS spoofing detection using a maximum likelihood-based sliding window method |
title_fullStr | GNSS spoofing detection using a maximum likelihood-based sliding window method |
title_full_unstemmed | GNSS spoofing detection using a maximum likelihood-based sliding window method |
title_short | GNSS spoofing detection using a maximum likelihood-based sliding window method |
title_sort | gnss spoofing detection using a maximum likelihood-based sliding window method |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7454987/ https://www.ncbi.nlm.nih.gov/pubmed/32857756 http://dx.doi.org/10.1371/journal.pone.0237146 |
work_keys_str_mv | AT jeongseongkyun gnssspoofingdetectionusingamaximumlikelihoodbasedslidingwindowmethod |