Nudge Attacks on Point-Cloud DNNs

Understand

The wide adaption of 3D point-cloud data in safety-critical applications such as autonomous driving makes adversarial samples a real threat.

• Existing adversarial attacks on point clouds achieve high success rates but modify a large number of points, which is usually difficult to do in real-life scenarios.
• In this paper, we explore a family of attacks that only perturb a few points of an input point cloud, and name them nudge attacks.
• We demonstrate that nudge attacks can successfully flip the results of modern point-cloud DNNs.