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.

View More Papers

WIP: Interrupt Attack on TEE-protected Robotic Vehicles

Mulong Luo (Cornell University) and G. Edward Suh (Cornell University)

Read More

P4DDPI: Securing P4-Programmable Data Plane Networks via DNS Deep...

Ali AlSabeh (University of South Carolina), Elie Kfoury (University of South Carolina), Jorge Crichigno (University of South Carolina) and Elias Bou-Harb (University of Texas at San Antonio)

Read More

Demo #15: Remote Adversarial Attack on Automated Lane Centering

Yulong Cao (University of Michigan), Yanan Guo (University of Pittsburgh), Takami Sato (UC Irvine), Qi Alfred Chen (UC Irvine), Z. Morley Mao (University of Michigan) and Yueqiang Cheng (NIO)

Read More

Securing CAN Traffic on J1939 Networks

Jeremy Daily, David Nnaji, and Ben Ettlinger (Colorado State University)

Read More