CCS2025
SCOPE: Expanding Client-Side Post-Processing for Efficient Privacy-Preserving Model Inference
Shenchen Zhu, Kai Chen, Yue Zhao, Cheng'an Wei
Abstract
Privacy-Preserving Inference (PPI) enables users to leverage powerful machine learning models without revealing sensitive input data. However, existing state-of-the-art solutions remain impractical due to significant computation and communication overheads.