21 citations · 21 across the 5 of their papers we have counts for
5 papers · 1 filter
Guard-GBDT: Efficient Privacy-Preserving Approximated GBDT Training on Vertical Dataset
Anxiao Song, Shujie Cui, Jianli Bai +3
In light of increasing privacy concerns and stringent legal regulations, using secure multiparty computation (MPC) to enable collaborative GBDT model training among multiple data o…
Mostree : Malicious Secure Private Decision Tree Evaluation with Sublinear Communication
Jianli Bai, Xiangfu Song, Xiaowu Zhang +4
A private decision tree evaluation (PDTE) protocol allows a feature vector owner (FO) to classify its data using a tree model from a model owner (MO) and only reveals an inference…
CryptoMask : Privacy-preserving Face Recognition
Jianli Bai, Xiaowu Zhang, Xiangfu Song +4
Face recognition is a widely-used technique for identification or verification, where a verifier checks whether a face image matches anyone stored in a database. However, in scenar…
GTree: GPU-Friendly Privacy-preserving Decision Tree Training and Inference
Qifan Wang, Shujie Cui, Lei Zhou +4
Decision tree (DT) is a widely used machine learning model due to its versatility, speed, and interpretability. However, for privacy-sensitive applications, outsourcing DT training…
Scalable Private Decision Tree Evaluation with Sublinear Communication
Jianli Bai, Xiangfu Song, Shujie Cui +2
Private decision tree evaluation (PDTE) allows a decision tree holder to run a secure protocol with a feature provider. By running the protocol, the feature provider will learn a c…