On the Limitations of Denoising Strategies as Adversarial Defenses

On the Limitations of Denoising Strategies as Adversarial Defenses

17 December 2020

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Papers citing "On the Limitations of Denoising Strategies as Adversarial Defenses"

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Title
A Random Ensemble of Encrypted Vision Transformers for Adversarially Robust Defense Ryota Iijima Sayaka Shiota Hitoshi Kiya 92 6 0 11 Feb 2024
Efficient Key-Based Adversarial Defense for ImageNet by Using Pre-trained Model AprilPyone Maungmaung Isao Echizen Hitoshi Kiya VLM AAML 57 0 0 28 Nov 2023
Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness Ambar Pal Huaijin Hao Rene Vidal 93 8 0 28 Sep 2023
Hindering Adversarial Attacks with Multiple Encrypted Patch Embeddings AprilPyone Maungmaung Isao Echizen Hitoshi Kiya AAML 59 2 0 04 Sep 2023
Hindering Adversarial Attacks with Implicit Neural Representations Andrei A. Rusu D. A. Calian Sven Gowal R. Hadsell AAML 165 4 0 22 Oct 2022
Reverse Engineering of Imperceptible Adversarial Image Perturbations Yifan Gong Yuguang Yao Yize Li Yimeng Zhang Xiaoming Liu Xinyu Lin Sijia Liu AAML 172 21 0 26 Mar 2022
$Reverse Engineering $\ell_p$ attacks: A block-sparse optimization approach with recovery guarantees$ Reverse Engineering $\ell_p$ attacks: A block-sparse optimization approach with recovery guarantees D. Thaker Paris V. Giampouras René Vidal AAML 31 6 0 09 Mar 2022
Dual Head Adversarial Training Yujing Jiang Xingjun Ma S. Erfani James Bailey AAML 45 4 0 21 Apr 2021
RAILS: A Robust Adversarial Immune-inspired Learning System Ren Wang Tianqi Chen Stephen Lindsly A. Rehemtulla Alfred Hero I. Rajapakse AAML 30 7 0 18 Dec 2020
Towards Robust Neural Networks via Orthogonal Diversity Kun Fang Qinghua Tao Yingwen Wu Tao Li Jia Cai Feipeng Cai Xiaolin Huang Jie Yang AAML 80 8 0 23 Oct 2020