226 citations · 395 across the 6 of their papers we have counts for
7 papers
You Can't See Me: Physical Removal Attacks on LiDAR-based Autonomous Vehicles Driving Frameworks
Yulong Cao, S. Hrushikesh Bhupathiraju, Pirouz Naghavi +3
Autonomous Vehicles (AVs) increasingly use LiDAR-based object detection systems to perceive other vehicles and pedestrians on the road. While existing attacks on LiDAR-based autono…
AdvDO: Realistic Adversarial Attacks for Trajectory Prediction
Yulong Cao, Chaowei Xiao, Anima Anandkumar +2
Trajectory prediction is essential for autonomous vehicles (AVs) to plan correct and safe driving behaviors. While many prior works aim to achieve higher prediction accuracy, few s…
Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks
Yulong Cao*, Ningfei Wang*, Chaowei Xiao* +6
In Autonomous Driving (AD) systems, perception is both security and safety critical. Despite various prior studies on its security issues, all of them only consider attacks on came…
On Adversarial Robustness of 3D Point Cloud Classification under Adaptive Attacks
Jiachen Sun, Karl Koenig, Yulong Cao +2
3D point clouds play pivotal roles in various safety-critical applications, such as autonomous driving, which desires the underlying deep neural networks to be robust to adversaria…
Towards Robust LiDAR-based Perception in Autonomous Driving: General Black-box Adversarial Sensor Attack and Countermeasures
Jiachen Sun, Yulong Cao, Qi Alfred Chen +1
Perception plays a pivotal role in autonomous driving systems, which utilizes onboard sensors like cameras and LiDARs (Light Detection and Ranging) to assess surroundings. Recent s…
Adversarial Sensor Attack on LiDAR-based Perception in Autonomous Driving
Yulong Cao, Chaowei Xiao, Benjamin Cyr +6
In Autonomous Vehicles (AVs), one fundamental pillar is perception, which leverages sensors like cameras and LiDARs (Light Detection and Ranging) to understand the driving environm…