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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Demo #2: Policy-based Discovery and Patching of Logic Bugs...

Hyungsub Kim (Purdue University), Muslum Ozgur Ozmen (Purdue University), Antonio Bianchi (Purdue University), Z. Berkay Celik (Purdue University) and Dongyan Xu (Purdue University)

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Model-Agnostic Defense for Lane Detection against Adversarial Attack

Henry Xu, An Ju, and David Wagner (UC Berkeley) Baidu Security Auto-Driving Security Award Winner ($1000 cash prize)!

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Demo #13: Attacking LiDAR Semantic Segmentation in Autonomous Driving

Yi Zhu (State University of New York at Buffalo), Chenglin Miao (University of Georgia), Foad Hajiaghajani (State University of New York at Buffalo), Mengdi Huai (University of Virginia), Lu Su (Purdue University) and Chunming Qiao (State University of New York at Buffalo)

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VPNInspector: Systematic Investigation of the VPN Ecosystem

Reethika Ramesh (University of Michigan), Leonid Evdokimov (Independent), Diwen Xue (University of Michigan), Roya Ensafi (University of Michigan)

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