  In this study, we propose an innovative method for the real-time detection of
GPS spoofing attacks targeting drones, based on the video stream captured by a
drone's camera. The proposed method collects frames from the video stream and
their location (GPS); by calculating the correlation between each frame, our
method can identify an attack on a drone. We first analyze the performance of
the suggested method in a controlled environment by conducting experiments on a
flight simulator that we developed. Then, we analyze its performance in the
real world using a DJI drone. Our method can provide different levels of
security against GPS spoofing attacks, depending on the detection interval
required; for example, it can provide a high level of security to a drone
flying at an altitude of 50-100 meters over an urban area at an average speed
of 4 km/h in conditions of low ambient light; in this scenario, the method can
provide a level of security that detects any GPS spoofing attack in which the
spoofed location is a distance of 1-4 meters (an average of 2.5 meters) from
the real location.
