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

Trust the Crowd: Wireless Witnessing to Detect Attacks on...

Kai Jansen (Ruhr University Bochum), Liang Niu (New York University), Nian Xue (New York University), Ivan Martinovic (University of Oxford), Christina Pöpper (New York University Abu Dhabi)

All the Numbers are US: Large-scale Abuse of Contact...

Christoph Hagen (University of Würzburg), Christian Weinert (TU Darmstadt), Christoph Sendner (University of Würzburg), Alexandra Dmitrienko (University of Würzburg), Thomas Schneider (TU Darmstadt)

Practical Non-Interactive Searchable Encryption with Forward and Backward Privacy

Shi-Feng Sun (Monash University, Australia), Ron Steinfeld (Monash University, Australia), Shangqi Lai (Monash University, Australia), Xingliang Yuan (Monash University, Australia), Amin Sakzad (Monash University, Australia), Joseph Liu (Monash University, Australia), ‪Surya Nepal‬ (Data61, CSIRO, Australia), Dawu Gu (Shanghai Jiao Tong University, China)

Censored Planet: An Internet-wide, Longitudinal Censorship Observatory

R. Sundara Raman, P. Shenoy, K. Kohls, and R. Ensafi (University of Michigan)