Corpus ID: 220265571

Towards Robust LiDAR-based Perception in Autonomous Driving: General Black-box Adversarial Sensor Attack and Countermeasures

@article{Sun2020TowardsRL,
  title={Towards Robust LiDAR-based Perception in Autonomous Driving: General Black-box Adversarial Sensor Attack and Countermeasures},
  author={Jiachen Sun and Yulong Cao and Qi Alfred Chen and Z. Morley Mao},
  journal={ArXiv},
  year={2020},
  volume={abs/2006.16974}
}
  • Jiachen Sun, Yulong Cao, +1 author Z. Morley Mao
  • Published 2020
  • Computer Science
  • ArXiv
  • 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 studies have demonstrated that LiDAR-based perception is vulnerable to spoofing attacks, in which adversaries spoof a fake vehicle in front of a victim self-driving car by strategically transmitting laser signals to the victim’s LiDAR sensor. However, existing attacks suffer from effectiveness and generality… CONTINUE READING

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