An Evolutionary, Gradient-Free, Query-Efficient, Black-Box Algorithm for Generating Adversarial Instances in Deep Networks. (arXiv:2208.08297v2 [cs.CV] UPDATED)

Deep neural networks (DNNs) are sensitive to adversarial data in a variety of
scenarios, including the black-box scenario, where the attacker is only allowed
to query the trained model and receive an output. Existing black-box methods
for creating adversarial instances are costly, often using gradient estimation
or training a replacement network. This paper introduces
\textbf{Qu}ery-Efficient \textbf{E}volutiona\textbf{ry} \textbf{Attack},
\textit{QuEry Attack}, an untargeted, score-based, black-box attack. QuEry
Attack is based on a novel objective function that can be used in gradient-free
optimization …

algorithm arxiv free gradient networks query