Abstract
The UAV security problem is becoming more and more serious, and the security of sensors is receiving much attention. UAV's operation depends on the data collected by sensors, and spoofed data is prone to lead UAV making wrong decisions. In order to detect sensor spoofing, we propose a drone sensor spoofing detection (SSDGOF) algorithm based on GPS and optical flow fusion. In SSDGOF, the fusion model of GPS and optical flow raw data is compared with the model of fusion data in the normal state of the drone, and the difference between them is used to determine whether the sensor was attacked. The SSDGOF is evaluated through GPS deception experiments, and the results show that this method is superior to other methods in detection efficiency.
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