24 citations · 24 across the 2 of their papers we have counts for
2 papers
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.CR2022★ 24 cited
pMPL: A Robust Multi-Party Learning Framework with a Privileged Party
Lushan Song, Jiaxuan Wang, Zhexuan Wang +5
In order to perform machine learning among multiple parties while protecting the privacy of raw data, privacy-preserving machine learning based on secure multi-party computation (M…