EMPSI: Efficient multiparty private set intersection (with cardinality)

作者：Yang, Yunbo; Dong, Xiaolei^*; Cao, Zhenfu^*; Shen, Jiachen^*; Li, Ruofan; Yang, Yihao; Dou, Shangmin

来源：Frontiers of Computer Science, 2024, 18(1): 181804.

DOI：10.1007/s11704-022-2269-0

Multiparty private set intersection (PSI) allows several parties, each holding a set of elements, to jointly compute the intersection without leaking any additional information. With the development of cloud computing, PSI has a wide range of applications in privacy protection. However, it is complex to build an efficient and reliable scheme to protect user privacy.To address this issue, we propose EMPSI, an efficient PSI (with cardinality) protocol in a multiparty setting. EMPSI avoids using heavy cryptographic primitives (mainly rely on symmetric-key encryption) to achieve better performance. In addition, both PSI and PSI with the cardinality of EMPSI are secure against semi-honest adversaries and allow any number of colluding clients (at least one honest client). We also do experiments to compare EMPSI with some state-of-the-art works. The experimental results show that proposed EMPSI (-CA) has better performance and is scalable in the number of clients and the set size.