Renyang Liu

I am currently a Research Fellow at the Institute of Data Science, National University of Singapore, , under the supervision of Prof. See-Kiong Ng👨‍🏫 and collaborating closely with Prof. Tianwei Zhang👨‍🏫 from Nanyang Technological University, , Prof. Wenjie Feng👨‍🏫 form University of Science and Technology of China, . Before that, I received my PhD degree 🎓 at Yunnan University, , supervised by Prof. Wei Zhou 👨‍🔬. 📅 From 2022 to 2023, I was a visiting student at the College of Computing and Data Science, Nanyang Technological University, , under the supervision of Prof. LAM, Kwok Yan 👨‍🏫. 📅 From 2023 to 2024, I am a Research Intern at the School of Cyber Security, Sun Yat-sen University, , supervised by Prof. Ziyu Lvy👩‍🏫.

📍 Address: Innovation 4.0 🏢, #04-06, Research Link, Singapore 117602, Singapore

💡 Research Interests:

AI Security & Data Privacy 🔐
Machine Unlearning 🔄
Adversarial Attacks 🛡️

News

Jul 11, 2025	✨ Our latest paper, Image Can Bring Your Memory Back: A Novel Multi-Modal Guided Attack against Image Generation Model Unlearning, is now available! Check it out! ✨
Jul 05, 2025	One paper on AIGC natrualness evaluation has been accepted by ACM MM (CCF-A)! Thanks to Prof. Ziyu Lyu and other awesome collaborators. Check it out! ✨
May 28, 2025	One paper on Image Generation Model Unlearning has been accepted by ACM CCS (CCF-A, Big 4)! Thanks to Prof. Wenjie Feng and other awesome collaborators. Check it out! ✨
Sep 18, 2024	One paper has been accepted by TMM (SCI Q1, CCF-B, TOP)! Many thanks to my collaborators.
Aug 12, 2024	Start as a Research Fellow at the National University of Singapore. Looking forward to conducting exciting research on AI Security & Data Privacy with Prof. See-Kiong Ng in near future!
Jun 16, 2024	I was awarded the honor of Outstanding Ph.D. Graduate from Yunnan University! ✨

Selected Publications

MM 2025

D-Judge: How Far Are We? Evaluating the Discrepancies Between AI-synthesized Images and Natural Images through Multimodal Guidance

Renyang Liu, Ziyu Lyu, Wei Zhou, and See-Kiong Ng

In ACM International Conference on Multimedia (MM), 2025

Bib PDF Code

@inproceedings{liu2024anid,
  title = {D-Judge: How Far Are We? Evaluating the Discrepancies Between AI-synthesized Images and Natural Images through Multimodal Guidance},
  author = {Liu, Renyang and Lyu, Ziyu and Zhou, Wei and Ng, See-Kiong},
  booktitle = {ACM International Conference on Multimedia (MM)},
  organization = {ACM},
  year = {2025},
  data = {https://huggingface.co/datasets/Renyang/DANI},
}

CCS 2025

Rethinking Machine Unlearning in Image Generation Models

Renyang Liu, Wenjie Feng, Tianwei Zhang, Wei Zhou, Xueqi Cheng, and See-Kiong Ng

In ACM Conference on Computer and Communications Security (CCS), 2025

Bib PDF Code

@inproceedings{liu2025igmu,
  title = {Rethinking Machine Unlearning in Image Generation Models},
  author = {Liu, Renyang and Feng, Wenjie and Zhang, Tianwei and Zhou, Wei and Cheng, Xueqi and Ng, See-Kiong},
  booktitle = {ACM Conference on Computer and Communications Security (CCS)},
  organization = {ACM},
  year = {2025},
}

TMM 2025

STBA: Towards Evaluating the Robustness of DNNs for Query-Limited Black-box Scenario

Renyang Liu, Kwok-Yan Lam, Wei Zhou, Sixing Wu, Jun Zhao, Dongting Hu, and Mingming Gong

IEEE Transactions on Multimedia, 2025

Bib PDF Code

@article{liu2024stba,
  title = {STBA: Towards Evaluating the Robustness of DNNs for Query-Limited Black-box Scenario},
  author = {Liu, Renyang and Lam, Kwok-Yan and Zhou, Wei and Wu, Sixing and Zhao, Jun and Hu, Dongting and Gong, Mingming},
  journal = {IEEE Transactions on Multimedia},
  year = {2025},
  publisher = {IEEE},
}

TWC 2024

Post-Deployment Fine-Tunable Semantic Communication

Peiyuan Si, Renyang Liu, Liangxin Qian, Jun Zhao, and Kwok-Yan Lam

IEEE Transactions on Wireless Communications, 2024

Bib PDF

@article{si2024post,
  title = {Post-Deployment Fine-Tunable Semantic Communication},
  author = {Si, Peiyuan and Liu, Renyang and Qian, Liangxin and Zhao, Jun and Lam, Kwok-Yan},
  journal = {IEEE Transactions on Wireless Communications},
  year = {2024},
  publisher = {IEEE},
}

TIFS 2024

Boosting Black-box Attack to Deep Neural Networks with Conditional Diffusion Models

Renyang Liu, Wei Zhou, Tianwei Zhang, Kangjie Chen, Jun Zhao, and Kwok-Yan Lam

IEEE Transactions on Information Forensics and Security, 2024

Bib PDF Code

@article{liu2024boosting,
  title = {Boosting Black-box Attack to Deep Neural Networks with Conditional Diffusion Models},
  author = {Liu, Renyang and Zhou, Wei and Zhang, Tianwei and Chen, Kangjie and Zhao, Jun and Lam, Kwok-Yan},
  journal = {IEEE Transactions on Information Forensics and Security},
  year = {2024},
  publisher = {IEEE},
}

TDSC 2023

Type-I generative adversarial attack

Shenghong He, Ruxin Wang, Tongliang Liu, Chao Yi, Xin Jin, Renyang Liu, and Wei Zhou

IEEE Transactions on Dependable and Secure Computing, 2023

Bib PDF

@article{he2022type,
  title = {Type-I generative adversarial attack},
  author = {He, Shenghong and Wang, Ruxin and Liu, Tongliang and Yi, Chao and Jin, Xin and Liu, Renyang and Zhou, Wei},
  journal = {IEEE Transactions on Dependable and Secure Computing},
  volume = {20},
  number = {3},
  pages = {2593--2606},
  year = {2023},
  publisher = {IEEE},
}