GAN-based augmentation of poisoned 3D point cloud datasets amplifies attack effectiveness, increasing misclassification and operational impact on CAV decision-making by up to 3x compared to non-augmented baselines.
Rl-gan-net: A reinforcement learning agent controlled gan network for real-time point cloud shape completion,
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Assessing the Operational Impact of Poisoning Attacks over Augmented 3D Point Cloud Public Datasets for Connected and Autonomous Vehicles
GAN-based augmentation of poisoned 3D point cloud datasets amplifies attack effectiveness, increasing misclassification and operational impact on CAV decision-making by up to 3x compared to non-augmented baselines.