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

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)!

In this demo, we demonstrate how attackers can remotely apply split-second phantom attacks by embedding phantom road signs into an advertisement presented on an Internet connected digital billboard which causes Tesla’s autopilot to suddenly stop the car in the middle of a road.

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V2X Security: Status and Open Challenges

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…

KUBO: Precise and Scalable Detection of User-triggerable Undefined Behavior...

Changming Liu (Northeastern University), Yaohui Chen (Facebook Inc.), Long Lu (Northeastern University)

SODA: A Generic Online Detection Framework for Smart Contracts

Ting Chen (University of Electronic Science and Technology of China), Rong Cao (University of Electronic Science and Technology of China), Ting Li (University of Electronic Science and Technology of China), Xiapu Luo (The Hong Kong Polytechnic University), Guofei Gu (Texas A&M University), Yufei Zhang (University of Electronic Science and Technology of China), Zhou Liao (University…

RandRunner: Distributed Randomness from Trapdoor VDFs with Strong Uniqueness

Philipp Schindler (SBA Research), Aljosha Judmayer (SBA Research), Markus Hittmeir (SBA Research), Nicholas Stifter (SBA Research, TU Wien), Edgar Weippl (Universität Wien)