41 citations · 68 across the 8 of their papers we have counts for
7 papers · 1 filter
QuanShield: Protecting against Side-Channels Attacks using Self-Destructing Enclaves
Shujie Cui, Haohua Li, Yuanhong Li +3
Trusted Execution Environments (TEEs) allow user processes to create enclaves that protect security-sensitive computation against access from the OS kernel and the hypervisor. Rece…
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…
EnclaveTree: Privacy-preserving Data Stream Training and Inference Using TEE
Qifan Wang, Shujie Cui, Lei Zhou +3
The classification service over a stream of data is becoming an important offering for cloud providers, but users may encounter obstacles in providing sensitive data due to privacy…
Privacy-preserving Searchable Databases with Controllable Leakage
Shujie Cui, Xiangfu Song, Muhammad Rizwan Asghar +2
Searchable Encryption (SE) is a technique that allows Cloud Service Providers (CSPs) to search over encrypted datasets without learning the content of queries and records. In recen…