Abstract
Most of the existing GPS spoofing detection schemes are vulnerable to the complex generative GPS spoofing attack, and require additional auxiliary equipments and extensive signal processing capabilities, leading to defects such as low real-time performance and large communication overhead which may not be available for the unmanned aerial vehicle (UAV, also known as drone) system. Motivated by the limitations of prior work, we propose a GPS spoofing detection scheme that requires minimal prior configuration and employs information fusion based on the GPS receiver and inertial measurement unit (IMU). We use a real-time model of tracking and calculating to derive the current location of the drones which are then contrasted with the location information received by the GPS receiver to judge whether the UAV system is under spoofing attack. Experiments show that, while the accuracy meets the requirements of detection, the proposed method can accurately determine whether the system is attacked within 8 s, with a detection rate of 98.6%. Compared with the existing schemes, the performance of real-time detecting is improved in our method while the detection rate is ensured. Even in our worst-case, we detect GPS spoofing attack within 28 s after the UAV system starts its mission.
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Acknowledgment
This work were supported by National Natural Science Foundation of China (Grant Nos. U1708262, U1736203, 61772173, 61672413).
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Liang, C. et al. (2019). Detection of GPS Spoofing Attack on Unmanned Aerial Vehicle System. In: Chen, X., Huang, X., Zhang, J. (eds) Machine Learning for Cyber Security. ML4CS 2019. Lecture Notes in Computer Science(), vol 11806. Springer, Cham. https://doi.org/10.1007/978-3-030-30619-9_10
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DOI: https://doi.org/10.1007/978-3-030-30619-9_10
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