AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networkscs.CV
AutoZOOM reduces black-box attack query counts by 93% on MNIST, CIFAR-10, and ImageNet.
problem Efficiently attack black-box neural networks with minimal model queries.
method AutoZOOM uses an autoencoder and adaptive gradient estimation for query-efficient black-box attacks.
result Significant reduction in model queries (93%) without sacrificing attack success rate and visual quality.