WaNet -- Imperceptible Warping-based Backdoor Attack

Understand

With the thriving of deep learning and the widespread practice of using pre-trained networks, backdoor attacks have become an increasing security threat drawing many research interests in recent years.

• A third-party model can be poisoned in training to work well in normal conditions but behave maliciously when a trigger pattern appears.
• However, the existing backdoor attacks are all built on noise perturbation triggers, making them noticeable to humans.
• In this paper, we instead propose using warping-based triggers.