2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CR2022
SEEK: model extraction attack against hybrid secure inference protocols
Si Chen, Junfeng Fan
Security concerns about a machine learning model used in a prediction-as-a-service include the privacy of the model, the query and the result. Secure inference solutions based on h…
cs.CR2022
DHSA: Efficient Doubly Homomorphic Secure Aggregation for Cross-silo Federated Learning
Zizhen Liu, Si Chen, Jing Ye +3
Secure aggregation is widely used in horizontal Federated Learning (FL), to prevent leakage of training data when model updates from data owners are aggregated. Secure aggregation…
cs.CR2021★ 2 cited
SASH: Efficient Secure Aggregation Based on SHPRG For Federated Learning
Zizhen Liu, Si Chen, Jing Ye +3
To prevent private training data leakage in Fed?erated Learning systems, we propose a novel se?cure aggregation scheme based on seed homomor?phic pseudo-random generator (SHPRG), n…