Barak Davidovich (Ben-Gurion University of the Negev), Ben Nassi (Ben-Gurion University of the Negev) and Yuval Elovici (Ben-Gurion University of the Negev)

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 detect a GPS spoofing 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 proposed 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.

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Abbas Acar, Ege Tekiner, Selcuk Uluagac (Florida International University)

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Jonathan Petit (Director Of Engineering at Qualcomm Technologies) Dr. Jonathan Petit is Director of Engineering at Qualcomm Technologies, Inc., where he leads research in security of connected and automated vehicles (CAV). His team works on designing security solutions, but also develops tools for automotive penetration testing and builds prototypes. His recent work on misbehavior protection…

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Reflections on Artifact Evaluation

Dr. Eric Eide (University of Utah)

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