Global positioning system spoofing detection based on Support Vector Machines
Abstract The civil Global Positioning System (GPS) is vulnerable to spoofing because of its open signal structure. The performance of previous spoofing detection methods is often limited due to spoofing's strong concealment. In this study, a method is proposed to detect spoofing by analysing th...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-02-01
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| Series: | IET Radar, Sonar & Navigation |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/rsn2.12178 |
| _version_ | 1828433875892699136 |
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| author | Xuefen Zhu Teng Hua Fan Yang Gangyi Tu Xiyuan Chen |
| author_facet | Xuefen Zhu Teng Hua Fan Yang Gangyi Tu Xiyuan Chen |
| author_sort | Xuefen Zhu |
| collection | DOAJ |
| description | Abstract The civil Global Positioning System (GPS) is vulnerable to spoofing because of its open signal structure. The performance of previous spoofing detection methods is often limited due to spoofing's strong concealment. In this study, a method is proposed to detect spoofing by analysing the features of improved signal quality monitoring (SQM) moving variance (MV), improved SQM moving average (MA), early‐late phase, carrier‐to‐noise ratio–MV and clock offset rate of receiver using Support Vector Machines. Then, the effectiveness of different kernel functions is compared along with other previous methods, revealing that our method outperforms previous methods when coarse Gaussian is used as kernel function. Specifically, the f1 score of the proposed method is improved by 3.22%, 12.85% and 35.72% in comparison with Back Propagation network, Ratio and Delta. The authors hope this work is beneficial for future research and for the implementation of GPS spoofing detection technology and high‐performance receiver, which is of great significance to maintain the normal operation of GPS. |
| first_indexed | 2024-12-10T18:42:07Z |
| format | Article |
| id | doaj.art-94b1e37aed864646b250f7cd62b1f7dd |
| institution | Directory Open Access Journal |
| issn | 1751-8784 1751-8792 |
| language | English |
| last_indexed | 2024-12-10T18:42:07Z |
| publishDate | 2022-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Radar, Sonar & Navigation |
| spelling | doaj.art-94b1e37aed864646b250f7cd62b1f7dd2022-12-22T01:37:38ZengWileyIET Radar, Sonar & Navigation1751-87841751-87922022-02-0116222423710.1049/rsn2.12178Global positioning system spoofing detection based on Support Vector MachinesXuefen Zhu0Teng Hua1Fan Yang2Gangyi Tu3Xiyuan Chen4School of Instrument Science and Engineering Southeast University Nanjing ChinaSchool of Instrument Science and Engineering Southeast University Nanjing ChinaShanghai Aerospace Control Technology Institute Shanghai ChinaSchool of Electronic and Information Engineering Nanjing University of Information Science and Technology Nanjing ChinaSchool of Instrument Science and Engineering Southeast University Nanjing ChinaAbstract The civil Global Positioning System (GPS) is vulnerable to spoofing because of its open signal structure. The performance of previous spoofing detection methods is often limited due to spoofing's strong concealment. In this study, a method is proposed to detect spoofing by analysing the features of improved signal quality monitoring (SQM) moving variance (MV), improved SQM moving average (MA), early‐late phase, carrier‐to‐noise ratio–MV and clock offset rate of receiver using Support Vector Machines. Then, the effectiveness of different kernel functions is compared along with other previous methods, revealing that our method outperforms previous methods when coarse Gaussian is used as kernel function. Specifically, the f1 score of the proposed method is improved by 3.22%, 12.85% and 35.72% in comparison with Back Propagation network, Ratio and Delta. The authors hope this work is beneficial for future research and for the implementation of GPS spoofing detection technology and high‐performance receiver, which is of great significance to maintain the normal operation of GPS.https://doi.org/10.1049/rsn2.12178global position systemkernel functionsignal quality monitoringspoofingdetection |
| spellingShingle | Xuefen Zhu Teng Hua Fan Yang Gangyi Tu Xiyuan Chen Global positioning system spoofing detection based on Support Vector Machines IET Radar, Sonar & Navigation global position system kernel function signal quality monitoring spoofing detection |
| title | Global positioning system spoofing detection based on Support Vector Machines |
| title_full | Global positioning system spoofing detection based on Support Vector Machines |
| title_fullStr | Global positioning system spoofing detection based on Support Vector Machines |
| title_full_unstemmed | Global positioning system spoofing detection based on Support Vector Machines |
| title_short | Global positioning system spoofing detection based on Support Vector Machines |
| title_sort | global positioning system spoofing detection based on support vector machines |
| topic | global position system kernel function signal quality monitoring spoofing detection |
| url | https://doi.org/10.1049/rsn2.12178 |
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