Imperceptible and Robust Backdoor Attack in 3D Point Cloud. (arXiv:2208.08052v1 [cs.CV])

With the thriving of deep learning in processing point cloud data, recent
works show that backdoor attacks pose a severe security threat to 3D vision
applications. The attacker injects the backdoor into the 3D model by poisoning
a few training samples with trigger, such that the backdoored model performs
well on clean samples but behaves maliciously when the trigger pattern appears.
Existing attacks often insert some additional points into the point cloud as
the trigger, or utilize a linear transformation …

3d attack backdoor cloud