Yuntao Du (杜云滔)

Publications

The complete publication list can be found on Google Scholar. Also browse publications by year.
^* equal contribution, ^† mentored student

AI Security & Safety

1. Automated Profile Inference with Language Model Agents
   Yuntao Du, Zitao Li, Bolin Ding, Yaliang Li, Hanshen Xiao, Jingren Zhou, Ninghui Li
   ACL 2026 (Findings)  [pdf]  [code]
   AI Security & Safety First study showing that LLM agents enable automated doxing at web scale.
2. Beyond Data Privacy: New Privacy Risks for Large Language Models
   Yuntao Du, Zitao Li, Ninghui Li, Bolin Ding
   Data Eng. Bulletin 2025  [pdf]
   AI Security & Safety Systematizes new privacy risks of LLM agents beyond training-data leakage.

Machine Learning Privacy

1. On the Security of Dataset Membership Inference Protocols against Malicious Data Owners
   Patrick Li^†, Yuntao Du, Neil Gong
   Manuscript
2. Membership Inference Attacks Against Fine-tuned Diffusion-Based Language Models
   Yuetian Chen, Kaiyuan Zhang, Yuntao Du, Edoardo Stoppa, Charles Fleming, Ashish Kundu, Bruno Ribeiro, Ninghui Li
   ICLR 2026  [pdf]  [code]
3. Imitative Membership Inference Attack
   Yuntao Du, Yuetian Chen, Hanshen Xiao, Bruno Ribeiro, Ninghui Li
   USENIX Security 2026  [pdf]  [code]  [blog]
   Machine Learning Privacy A new shadow training paradigm for MIAs with significantly reduced computation.
4. Window-based Membership Inference Attacks Against Fine-tuned Large Language Models
   Yuetian Chen, Yuntao Du, Kaiyuan Zhang, Ashish Kundu, Charles Fleming, Bruno Ribeiro, Ninghui Li
   USENIX Security 2026  [pdf]  [code]
5. Membership Inference Attacks on Tokenizers of Large Language Models
   Meng Tong^*†, Yuntao Du^*, Kejiang Chen, Weiming Zhang, Ninghui Li
   USENIX Security 2026  [pdf]  [code]
   Machine Learning Privacy First study showing the privacy risk of LLM tokenizers.
6. Cascading and Proxy Membership Inference Attacks
   Yuntao Du, Jiacheng Li, Yuetian Chen, Kaiyuan Zhang, Zhizhen Yuan, Hanshen Xiao, Bruno Ribeiro, Ninghui Li
   NDSS 2026  [pdf]  [code]  [blog]
   Machine Learning Privacy Formulates and categorizes MIAs and first exploits membership dependencies.
7. SOFT: Selective Data Obfuscation for Protecting LLM Fine-tuning against Membership Inference Attacks
   Kaiyuan Zhang, Siyuan Cheng, Hanxi Guo, Yuetian Chen, Zian Su, Shengwei An, Yuntao Du, Charles Fleming, Ashish Kundu, Xiangyu Zhang, Ninghui Li
   USENIX Security 2025  [pdf]  [code]

Data Privacy

1. Privacy Leakage from a Thousand Words: Sub-Pixel Location Recovery from Dot Maps
   Yuntao Du^*, Tanishq Praveen Pauskar^*†, Hao Wang, Jing Su, Ninghui Li
   Manuscript
   Data Privacy First to identify re-identification risks of dot maps with 1-meter accuracy on national-scale maps.
2. Systematic Assessment of Tabular Data Synthesis
   Yuntao Du, Ninghui Li
   CCS 2025  [pdf]  [code]  [blog]
   Data Privacy Proposes a unified evaluation framework for tabular data synthesis algorithms.
3. Real-Time Trajectory Synthesis with Local Differential Privacy
   Yujia Hu^†, Yuntao Du, Zhikun Zhang, Ziquan Fang, Lu Chen, Kai Zheng, Yunjun Gao
   ICDE 2024  [pdf]  [code]
4. LDPTrace: Locally Differentially Private Trajectory Synthesis
   Yuntao Du, Yujia Hu^†, Zhikun Zhang, Ziquan Fang, Lu Chen, Baihua Zheng, Yunjun Gao
   VLDB 2023  [pdf]  [code]  [blog]
5. FLBooster: A Unified and Efficient Platform for Federated Learning Acceleration
   Zhihao Zeng^†, Yuntao Du, Ziquan Fang, Lu Chen, Shiliang Pu, Guodong Chen, Hui Wang, Yunjun Gao
   ICDE 2023  [pdf]

Recommender Systems

1. Knowledge-refined Denoising Network for Robust Recommendation
   Xinjun Zhu^†, Yuntao Du, Lu Chen, Baihua Zheng, Yunjun Gao
   SIGIR 2023  [pdf]  [code]
2. Towards Explainable Collaborative Filtering with Taste Clusters Learning
   Yuntao Du, Jianxun Lian, Jing Yao, Xiting Wang, Mingqi Wu, Lu Chen, Yunjun Gao, Xing Xie
   WWW 2023  [pdf]  [code]
3. HAKG: Hierarchy-Aware Knowledge Gated Network for Recommendation
   Yuntao Du, Xinjun Zhu^†, Lu Chen, Baihua Zheng, Yunjun Gao
   SIGIR 2022  [pdf]  [code]
4. Self-Guided Learning to Denoise for Robust Recommendation
   Yunjun Gao, Yuntao Du, Yujia Hu, Lu Chen, Xinjun Zhu, Ziquan Fang, Baihua Zheng
   SIGIR 2022  [pdf]  [code]
5. MetaKG: Meta-learning on Knowledge Graph for Cold-start Recommendation
   Yuntao Du, Xinjun Zhu^†, Lu Chen, Ziquan Fang, Yunjun Gao
   TKDE 2023  [pdf]  [code]

Spatio-temporal Data Mining

1. Spatio-Temporal Trajectory Similarity Learning in Road Networks
   Ziquan Fang, Yuntao Du, Xinjun Zhu, Danlei Hu, Lu Chen, Yunjun Gao, Christian S. Jensen
   SIGKDD 2022  [pdf]  [code]
2. E2DTC: An End to End Deep Trajectory Clustering Framework via Self-Training
   Ziquan Fang, Yuntao Du, Lu Chen, Yujia Hu, Yunjun Gao, Gang Chen
   ICDE 2021  [pdf]  [code]
3. MDTP: A Multi-source Deep Traffic Prediction Framework over Spatio-Temporal Trajectory Data
   Ziquan Fang, Lu Pan, Lu Chen, Yuntao Du, Yunjun Gao
   VLDB 2021  [pdf]