Publications

Conference

HawkEye: Statically and Accurately Profiling the Communication Cost of Models in Multi-party Learning. Wenqiang Ruan, Xin Lin, Ruisheng Zhou, Guopeng Lin, Shui Yu, Weili Han. In Proceedings of the 34th USENIX Security, Seattle, WA, USA, August 13–15, 2025: 2673-2691.

Ents: An Efficient Three-party Training Framework for Decision Trees by Communication Optimization. Guopeng Lin, Weili Han, Wenqiang Ruan, Ruisheng Zhou, Lushan Song, Bingshuai Li, Yunfeng Shao. In Proceedings of the 31th ACM Conference on Computer and Communications Security (CCS 2024), Salt Lake City, UT, USA, October 14-18, 2024: 4376–4390. (Distinguished Artifact Award)

Digit Semantics based Optimization for Practical Password Cracking Tools; Haodong Zhang, Chuanwang Wang, Wenqiang Ruan, Junjie Zhang, Ming Xu, Weili Han; In Annual Computer Security Applications Conference (ACSAC ’21) link

pMPL: A Robust Multi-Party Learning Framework with a Privileged Party; Lushan Song, Jiaxuan Wang, Zhexuan Wang, Xinyu Tu, Guopeng Lin, Wenqiang Ruan, Haoqi Wu, Weili Han; In Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security November 7–11, 2022 (ACM CCS 2022) link

Private, Efficient, and Accurate: Protecting Models Trained by Multi-party Learning with Differential Privacy; Wenqiang Ruan, Mingxin Xu, Wenjing Fang, Li Wang, Lei Wang, Weili Han; In Proceedings of The 44th IEEE Symposium on Security and Privacy (IEEE S&P 2023) link

Journal

Towards Understanding the Fairness of Differentially Private Margin Classifiers; Wenqiang Ruan, Mingxin Xu, Yinan Jing, Weili Han; In World Wide Web Journal (WWWJ), 2022 link

Secure Multi-party Learning: From Secure Computation to Secure Learning; Weili Han, Lushan Song, Wenqiang Ruan, Guopeng Lin, Zhexuan Wang; In Journal of Computer Science and Technology, 2023

Magazine

Privacy Compliance: Can Technology Come to the Rescue?; Wenqiang Ruan, Mingxin Xu, Haoyang Jia, Zhenhuan Wu, LuShan Song, Weili Han; In IEEE Security & Privacy 2021 link

Preprint

SoK: Training Machine Learning Models over Multiple Sources with Privacy Preservation; Lushan Song, Haoqi Wu, Wenqiang Ruan, Weili Han arxiv