Adversarial Attacks and Defenses in Machine Learning-Powered Networks: A Contemporary Survey

11 March 2023

Papers citing "Adversarial Attacks and Defenses in Machine Learning-Powered Networks: A Contemporary Survey"

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Title
Unveiling and Mitigating Adversarial Vulnerabilities in Iterative Optimizers Elad Sofer Tomer Shaked Caroline Chaux Nir Shlezinger AAML 33 0 0 26 Apr 2025
A Survey on Physical Adversarial Attack in Computer Vision Donghua Wang Wen Yao Tingsong Jiang Guijian Tang Xiaoqian Chen AAML 51 32 0 28 Sep 2022
Wild Networks: Exposure of 5G Network Infrastructures to Adversarial Examples Giovanni Apruzzese Rodion Vladimirov A.T. Tastemirova P. Laskov AAML 8 14 0 04 Jul 2022
A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies Zhuang Qian Kaizhu Huang Qiufeng Wang Xu-Yao Zhang OOD AAML ObjD 44 71 0 26 Mar 2022
An Intermediate-level Attack Framework on The Basis of Linear Regression Yiwen Guo Qizhang Li W. Zuo Hao Chen 23 13 0 21 Mar 2022
Adaptive Adversarial Training for Meta Reinforcement Learning Shiqi Chen Zhengyu Chen Donglin Wang 15 6 0 27 Apr 2021
Random Projections for Improved Adversarial Robustness Ginevra Carbone G. Sanguinetti Luca Bortolussi AAML 13 2 0 18 Feb 2021
Adversarial Camouflage: Hiding Physical-World Attacks with Natural Styles Ranjie Duan Xingjun Ma Yisen Wang James Bailey •. A. K. Qin Yun Yang AAML 151 222 0 08 Mar 2020
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 256 3,102 0 04 Nov 2016