Detection of adversarial attacks via disentangling natural images and perturbations

The vulnerability of deep neural networks against adversarial attacks, i.e., imperceptible adversarial perturbations can easily give rise to wrong predictions, poses a huge threat to the security of their real-world deployments. In this paper, a novel Adversarial Detection method via Disentangling N...

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Main Authors: Qing, Yuanyuan, Bai, Tao, Liu, Zhuotao, Moulin, Pierre, Wen, Bihan
其他作者: School of Electrical and Electronic Engineering
格式: Article
語言:English
出版: 2024
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在線閱讀:https://hdl.handle.net/10356/178082
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