3 papers
cs.CR2026
Bifrost: A Much Simpler Secure Two-Party Data Join Protocol for Secure Data Analytics
Shuyu Chen, Mingxun Zhou, Haoyu Niu +2
Secure data join enables two parties with vertically distributed data to securely compute the joined table, allowing the parties to perform downstream Secure multi-party computatio…
cs.CR2025
IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning
Shuyu Chen, Guopeng Lin, Haoyu Niu +3
Vertical privacy-preserving machine learning (vPPML) enables multiple parties to train models on their vertically distributed datasets while keeping datasets private. In vPPML, it…
cs.CR2025
HawkEye: Statically and Accurately Profiling the Communication Cost of Models in Multi-party Learning
Wenqiang Ruan, Xin Lin, Ruisheng Zhou +3
Multi-party computation (MPC) based machine learning, referred to as multi-party learning (MPL), has become an important technology for utilizing data from multiple parties with pr…