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20202025
most citedIntellectual Property Protection for Deep Learning Models: Taxonomy, Methods, Attacks, and Evaluations

76 citations · 292 across the 19 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

cs.CV2022★ 6 cited

InFIP: An Explainable DNN Intellectual Property Protection Method based on Intrinsic Features

Mingfu Xue, Xin Wang, Yinghao Wu +3

Intellectual property (IP) protection for Deep Neural Networks (DNNs) has raised serious concerns in recent years. Most existing works embed watermarks in the DNN model for IP prot…

cs.MM2022

Adaptive 3D Mesh Steganography Based on Feature-Preserving Distortion

Yushu Zhang, Jiahao Zhu, Mignfu Xue +2

Current 3D mesh steganography algorithms relying on geometric modification are prone to detection by steganalyzers. In traditional steganography, adaptive steganography has proven…

cs.CV2022★ 2 cited

Detecting Recolored Image by Spatial Correlation

Yushu Zhang, Nuo Chen, Shuren Qi +2

Image forensics, aiming to ensure the authenticity of the image, has made great progress in dealing with common image manipulation such as copy-move, splicing, and inpainting in th…

cs.CV2022★ 8 cited

Imperceptible and Multi-channel Backdoor Attack against Deep Neural Networks

Mingfu Xue, Shifeng Ni, Yinghao Wu +3

Recent researches demonstrate that Deep Neural Networks (DNN) models are vulnerable to backdoor attacks. The backdoored DNN model will behave maliciously when images containing bac…

cs.CV2022★ 16 cited

Compression-Resistant Backdoor Attack against Deep Neural Networks

Mingfu Xue, Xin Wang, Shichang Sun +3

In recent years, many backdoor attacks based on training data poisoning have been proposed. However, in practice, those backdoor attacks are vulnerable to image compressions. When…