Type-I Generative Adversarial Attack

Author:

He Shenghong1,Wang Ruxin1ORCID,Liu Tongliang2ORCID,Yi Chao1,Jin Xin1,Liu Renyang3,Zhou Wei1ORCID

Affiliation:

1. School of Software and the Engineering Research Center of Cyberspace, Yunnan University, Kunming, China

2. UBTECH Sydney Artificial Intelligence Centre, School of Computer Science, Faculty of Engineering, University of Sydney, 6 Cleveland St, Darlington, NSW, Australia

3. Information Science and Engineering School, Yunnan University, Kunming, China

Funder

National Natural Science Foundation of China

Yunnan Province Science Foundation for Youths

Open Foundation of Key Laboratory in Software Engineering of Yunnan Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Exploiting Type I Adversarial Examples to Hide Data Information: A New Privacy-Preserving Approach;IEEE Transactions on Emerging Topics in Computational Intelligence;2024-06

2. CNFA: Conditional Normalizing Flow for Query-Limited Attack;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

3. Gradient-guided hierarchical feature attack for object detector;Journal of King Saud University - Computer and Information Sciences;2024-01

4. The Impact of Adversarial Attacks on Federated Learning: A Survey;IEEE Transactions on Pattern Analysis and Machine Intelligence;2023

5. AFLOW: Developing Adversarial Examples Under Extremely Noise-Limited Settings;Information and Communications Security;2023

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