How to control the pixel number to be noised ? about nn_robust_attacks HOT 2 CLOSED

There are two types of attacks:

1. Maximize adversarialness subject to the distortion being less than some threshold.
2. Minimize distortion subject to the image being adversarial.

This attack is of the second flavor. So you can't directly control how many pixels are perturbed, it will keep shrinking the number of pixels until it can't succeed any more.

The simplest thing to do is just to run the attack and then at the end check if the number of pixels that changed is less than your threshold. If yes, the attack succeeded. Slightly more efficient would be to add an extra check around here
https://github.com/carlini/nn_robust_attacks/blob/master/l0_attack.py#L228
That will break out of the loop if equal_count > threshold.

from nn_robust_attacks.

There are two types of attacks:

1. Maximize adversarialness subject to the distortion being less than some threshold.
2. Minimize distortion subject to the image being adversarial.

This attack is of the second flavor. So you can't directly control how many pixels are perturbed, it will keep shrinking the number of pixels until it can't succeed any more.

The simplest thing to do is just to run the attack and then at the end check if the number of pixels that changed is less than your threshold. If yes, the attack succeeded. Slightly more efficient would be to add an extra check around here
https://github.com/carlini/nn_robust_attacks/blob/master/l0_attack.py#L228
That will break out of the loop if equal_count > threshold.

Yes, I have tried this method as your instruction and the result is okay!

equal_count = self.image_size**2-np.sum(np.all(np.abs(img-nimg[0])<.0001,axis=2)) 
if equal_count <threshold:
      return last_solution

Thanks so much !

from nn_robust_attacks.