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Towards Understanding and Harnessing the Effect of Image Transformation in Adversarial Detection
[article]
2022
arXiv
pre-print
Deep neural networks (DNNs) are threatened by adversarial examples. Adversarial detection, which distinguishes adversarial images from benign images, is fundamental for robust DNN-based services. Image transformation is one of the most effective approaches to detect adversarial examples. During the last few years, a variety of image transformations have been studied and discussed to design reliable adversarial detectors. In this paper, we systematically synthesize the recent progress on
arXiv:2201.01080v3
fatcat:sgrnmmtqb5hevavr5oyjyskfya