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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 2020Show all

5 papers · 1 filter

cs.CV2020★ 2 cited

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…

cs.CR2020★ 11 cited

Use the Spear as a Shield: A Novel Adversarial Example based Privacy-Preserving Technique against Membership Inference Attacks

Mingfu Xue, Chengxiang Yuan, Can He +4

Recently, the membership inference attack poses a serious threat to the privacy of confidential training data of machine learning models. This paper proposes a novel adversarial ex…

cs.CV2020★ 8 cited

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…

cs.CV2020★ 18 cited

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…

cs.CR2020★ 76 cited

Intellectual Property Protection for Deep Learning Models: Taxonomy, Methods, Attacks, and Evaluations

Mingfu Xue, Yushu Zhang, Jian Wang +1

The training and creation of deep learning model is usually costly, thus it can be regarded as an intellectual property (IP) of the model creator. However, malicious users who obta…