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.

Paper

View More Papers

Screen Gleaning: Receiving and Interpreting Pixels by Eavesdropping on...

Zhuoran Liu, Léo Weissbart, Dirk Lauret (Radboud University)

A Balanced DNS Information Protection Strategy: Minimize at Root...

S. Hollenbeck, B. Kalinski (Verisign)

Detecting Tor Bridge from Sampled Traffic in Backbone Networks

Hua Wu (School of Cyber Science & Engineering and Key Laboratory of Computer Network and Information Integration Southeast University, Ministry of Education, Jiangsu Nanjing, Purple Mountain Laboratories for Network and Communication Security (Nanjing, Jiangsu)), Shuyi Guo, Guang Cheng, Xiaoyan Hu (School of Cyber Science & Engineering and Key Laboratory of Computer Network and Information Integration…

FlowLens: Enabling Efficient Flow Classification for ML-based Network Security...

Diogo Barradas (INESC-ID, Instituto Superior Técnico, Universidade de Lisboa), Nuno Santos (INESC-ID, Instituto Superior Técnico, Universidade de Lisboa), Luis Rodrigues (INESC-ID, Instituto Superior Técnico, Universidade de Lisboa), Salvatore Signorello (LASIGE, Faculdade de Ciências, Universidade de Lisboa), Fernando M. V. Ramos (INESC-ID, Instituto Superior Técnico, Universidade de Lisboa), André Madeira (INESC-ID, Instituto Superior Técnico, Universidade de…