Global positioning system spoofing detection based on Support Vector Machines
| Autor: | Teng Hua, Xuefen Zhu, Xiyuan Chen, Fan Yang, Gangyi Tu |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
global position system
Spoofing attack business.industry Computer science detection signal quality monitoring spoofing TK5101-6720 Global position system Support vector machine kernel function Telecommunication Global Positioning System Computer vision Artificial intelligence Electrical and Electronic Engineering business |
| Zdroj: | IET Radar, Sonar & Navigation, Vol 16, Iss 2, Pp 224-237 (2022) |
| ISSN: | 1751-8792 1751-8784 |
| DOI: | 10.1049/rsn2.12178 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Plný text