Generative Dynamic Patch Attack

Understand

Adversarial patch attack is a family of attack algorithms that perturb a part of image to fool a deep neural network model.

• Existing patch attacks mostly consider injecting adversarial patches at input-agnostic locations: either a predefined location or a random location.
• This attack setup may be sufficient for attack but has considerable limitations when using it for adversarial training.
• Thus, robust models trained with existing patch attacks cannot effectively defend other adversarial attacks.