76 citations · 290 across the 16 of their papers we have counts for
7 papers · 1 filter
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…
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…
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…
Detecting Backdoor in Deep Neural Networks via Intentional Adversarial Perturbations
Mingfu Xue, Yinghao Wu, Zhiyu Wu +3
Recent researches show that deep learning model is susceptible to backdoor attacks. Many defenses against backdoor attacks have been proposed. However, existing defense works requi…
3D Invisible Cloak
Mingfu Xue, Can He, Zhiyu Wu +3
In this paper, we propose a novel physical stealth attack against the person detectors in real world. The proposed method generates an adversarial patch, and prints it on real clot…
SocialGuard: An Adversarial Example Based Privacy-Preserving Technique for Social Images
Mingfu Xue, Shichang Sun, Zhiyu Wu +3
The popularity of various social platforms has prompted more people to share their routine photos online. However, undesirable privacy leakages occur due to such online photo shari…
NaturalAE: Natural and Robust Physical Adversarial Examples for Object Detectors
Mingfu Xue, Chengxiang Yuan, Can He +2
In this paper, we propose a natural and robust physical adversarial example attack method targeting object detectors under real-world conditions. The generated adversarial examples…