Publication Type
Journal Article
Version
publishedVersion
Publication Date
3-2026
Abstract
Various services, such as search engines, are increasingly deployed in cloud-based and distributed systems. However, data are typically managed by trusted servers, making user privacy and data security critical concerns. Private set intersection (PSI) is a powerful cryptographic primitive that enables multiple parties to compute the intersection of their datasets without revealing private inputs. It has been extensively studied over the past two decades, leading to significant gains in computational and communication efficiency. Yet, in many real-world scenarios, revealing the raw intersection may still leak sensitive information. To address this, numerous PSI variants have been developed to meet different application needs. In this paper, we present a comprehensive survey of PSI and its variants. We categorize existing protocols by functionality and underlying cryptographic techniques and analyze their theoretical properties. We focus on recent developments from the last five years, including emerging directions such as fuzzy PSI and updatable PSI. We also explore applications of these protocols across various domains. Finally, we identify key research challenges, including improving privacy guarantees, enhancing computational efficiency, and ensuring scalability for large-scale datasets. These findings aim to guide future research, as PSI and its variants play a central role in advancing privacy-preserving applications.
Keywords
Private set intersection, Multiparty computation
Discipline
Databases and Information Systems | Information Security
Research Areas
Cybersecurity
Publication
Chinese Journal of Electronics
Volume
35
Issue
2
First Page
651
Last Page
667
ISSN
1022-4653
Identifier
10.23919/cje.2025.00.148
Citation
YANG, Yunbo; ZHU, Defan; NING, Jianting; FENG, Qi; LI, Xiaoguo; CHENG, Yuejia; YANG, Guomin; and REN, Kui.
Private set intersection: A systematic review. (2026). Chinese Journal of Electronics. 35, (2), 651-667.
Available at: https://ink.library.smu.edu.sg/sis_research/11252
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.23919/cje.2025.00.148