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20202022
most citedRobust Backdoor Attacks against Deep Neural Networks in Real Physical World

34 citations · 107 across the 6 of their papers we have counts for

collaborators

6 papers

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…

cs.MM2021★ 10 cited

Detect and remove watermark in deep neural networks via generative adversarial networks

Haoqi Wang, Mingfu Xue, Shichang Sun +3

Deep neural networks (DNN) have achieved remarkable performance in various fields. However, training a DNN model from scratch requires a lot of computing resources and training dat…

cs.AI2021★ 30 cited

Protecting the Intellectual Properties of Deep Neural Networks with an Additional Class and Steganographic Images

Shichang Sun, Mingfu Xue, Jian Wang +1

Recently, the research on protecting the intellectual properties (IP) of deep neural networks (DNN) has attracted serious concerns. A number of DNN copyright protection methods hav…

cs.CR2021★ 34 cited

Robust Backdoor Attacks against Deep Neural Networks in Real Physical World

Mingfu Xue, Can He, Shichang Sun +2

Deep neural networks (DNN) have been widely deployed in various applications. However, many researches indicated that DNN is vulnerable to backdoor attacks. The attacker can create…

cs.CR2021★ 9 cited

ActiveGuard: An Active DNN IP Protection Technique via Adversarial Examples

Mingfu Xue, Shichang Sun, Can He +3

The training of Deep Neural Networks (DNN) is costly, thus DNN can be considered as the intellectual properties (IP) of model owners. To date, most of the existing protection works…

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…