Towards Query-Efficient Black-Box Adversary with Zeroth-Order Natural Gradient Descent

Understand

Despite the great achievements of the modern deep neural networks (DNNs), the vulnerability/robustness of state-of-the-art DNNs raises security concerns in many application domains requiring high reliability.

• Various adversarial attacks are proposed to sabotage the learning performance of DNN models.
• Among those, the black-box adversarial attack methods have received special attentions owing to their practicality and simplicity.
• Black-box attacks usually prefer less queries in order to maintain stealthy and low costs.