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Beyond ImageNet Attack: Towards Crafting Adversarial Examples for Black-box Domains. (arXiv:2201.11528v1 [cs.CV])
Web: http://arxiv.org/abs/2201.11528
Jan. 28, 2022, 2:10 a.m. | Qilong Zhang, Xiaodan Li, Yuefeng Chen, Jingkuan Song, Lianli Gao, Yuan He, Hui Xue
cs.CV updates on arXiv.org arxiv.org
Adversarial examples have posed a severe threat to deep neural networks due
to their transferable nature. Currently, various works have paid great efforts
to enhance the cross-model transferability, which mostly assume the substitute
model is trained in the same domain as the target model. However, in reality,
the relevant information of the deployed model is unlikely to leak. Hence, it
is vital to build a more practical black-box threat model to overcome this
limitation and evaluate the vulnerability of deployed …
More from arxiv.org / cs.CV updates on arXiv.org
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