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Boosting Gradient for White-Box Adversarial Attacks
[article]
2020
arXiv
pre-print
Deep neural networks (DNNs) are playing key roles in various artificial intelligence applications such as image classification and object recognition. However, a growing number of studies have shown that there exist adversarial examples in DNNs, which are almost imperceptibly different from original samples, but can greatly change the network output. Existing white-box attack algorithms can generate powerful adversarial examples. Nevertheless, most of the algorithms concentrate on how to
arXiv:2010.10712v1
fatcat:5vigclzkarcxbompn4licfvecu