Ben Nassi, Dudi Nassi, Raz Ben Netanel and Yuval Elovici (Ben-Gurion University of the Negev)

In this paper, we evaluate the robustness of Mobileye 630 PRO, the most popular off-the-shelf ADAS on the market today, to camera spoofing attacks applied using a projector. We show that Mobileye 630 issues false notifications about road signs projected in proximity to the car that the system is installed in. We assess how changes of the road signs (e.g., changes in color, shape, projection speed, diameter and ambient light) affect the outcome of an attack. We find that while Mobileye 630 PRO rejects fake projected road signs that consists of non-original shapes and objects, it accepts fake projected road signs that consists of non-original colors. We demonstrate how attackers can leverage these findings to apply a remote attack in a realistic scenario by using a drone that carries a portable projector which projects the spoofed traffic sign on a building located in proximity to a passing car equipped with Mobileye 630. Our experiments show that it is possible to fool Mobileye 630 PRO to issue false notification about a traffic sign projected from a drone.

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Sn4ke: Practical Mutation Analysis of Tests at Binary Level

Mohsen Ahmadi (Arizona State University), Pantea Kiaei (Worcester Polytechnic Institute), Navid Emamdoost (University of Minnesota)

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Demo #4: Attacking Tesla Model X’s Autopilot Using Compromised...

Ben Nassi (Ben-Gurion University of the Negev), Yisroel Mirsky (Ben-Gurion University of the Negev, Georgia Tech), Dudi Nassi, Raz Ben Netanel (Ben-Gurion University of the Negev), Oleg Drokin (Independent Researcher), and Yuval Elovici (Ben-Gurion University of the Negev) Best Demo Award Winner ($300 cash prize)!

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Detecting CAN Masquerade Attacks with Signal Clustering Similarity

Pablo Moriano (Oak Ridge National Laboratory), Robert A. Bridges (Oak Ridge National Laboratory) and Michael D. Iannacone (Oak Ridge National Laboratory)

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