Frederik Diehl

Guessing Smart: Biased Sampling for Efficient Black-Box Adversarial Attacks

We consider adversarial examples for image classification in the black-box decision-based setting. Here, an attacker cannot access confidence scores, but only the final label. Most attacks for this scenario are either unreliable or inefficient. Focusing on the latter, we show that a specific class o…