Research on Outsourced PSI Protocols for Privacy Preserving Data Sharing

Abstract

Private set intersection (PSI), a basic privacy preserving technology for data sharing, is widely used in various practical applications such as educational system, anti-epidemic system and credit system. In traditional PSI solutions, two participants collaboratively calculate the intersection based on the plaintext sets they hold. In cloud computing scenario, cloud users would like to upload the encrypted data to the cloud rather than storing their own datasets locally, which needs to delegate cloud servers to execute PSI operations for data uses. Therefore, how to implement outsourced PSI computation is a hot topic of current research. In this paper, we mainly analyze the current researches focusing on the security and scalability of various existing out-sourced PSI protocols, including verifiable PSI, multi-party PSI, PSI-CA, quantum-based PSI, post-quantum-based PSI, fog-based PSI, blockchain-based PSI, attribute-based PSI, etc. Through the comparative analysis and summary of the existing schemes, we further discussed the future research direction.