The author introduces PCLD as a novel defense strategy for enhancing the robustness of 3D point cloud classification models against adversarial attacks by employing diffusion-based purification on a layerwise basis within neural network architecture.
3D point cloud models can be defended against adversarial attacks using the innovative PCLD method, enhancing robustness and performance.