Yulong Cao (University of Michigan), Ningfei Wang (UC, Irvine), Chaowei Xiao (Arizona State University), Dawei Yang (University of Michigan), Jin Fang (Baidu Research), Ruigang Yang (University of Michigan), Qi Alfred Chen (UC, Irvine), Mingyan Liu (University of Michigan) and Bo Li (University of Illinois at Urbana-Champaign)

In autonomous driving (AD) vehicles, Multi-Sensor Fusion (MSF) is used to combine perception results from multiple sensors such as LiDARs (Light Detection And Ranging) and cameras for both accuracy and robustness. In this work, we design the first attack that fundamentally defeats MSF-based AD perception by generating 3D adversarial objects. This demonstration will include video and figure demonstrations for the generated 3D adversarial objects and the end-to-end consequences.

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Demo #4: Recovering Autonomous Robotic Vehicles from Physical Attacks

Pritam Dash (University of British Columbia) and Karthik Pattabiraman (University of British Columbia)

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What Storage? An Empirical Analysis of Web Storage in...

Zubair Ahmad (Università Ca’ Foscari Venezia), Samuele Casarin (Università Ca’ Foscari Venezia), and Stefano Calzavara (Università Ca’ Foscari Venezia)

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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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