Anti-Inpainting: A Proactive Defense Approach Against Malicious Diffusion-Based Inpainters Under Unknown Conditions

IEEE Transactions on Dependable and Secure Computing 2026

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Authors: 郭益茂, Zuomin Qu, Wei Lü, Xiangyang Luo
DOI: 10.1109/tdsc.2026.3708852
Cited by: 1
References: 36

Fields of Study & Subjects

Generative Adversarial Networks and Image Synthesis Adversarial Robustness in Machine Learning Physical Unclonable Functions (PUFs) and Hardware Security

Publication details

Journal / source
IEEE Transactions on Dependable and Secure Computing
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
23
Issue
5
Pages
10988–11000
Publication date
1 July 2026