A scalable multiparty private set intersection

Abstract

Both scalability and flexibility become crucial for privacy preserving protocols in the age of Big Data. Private Set Intersection (PSI) is one of important privacy preserving protocols. Usually, PSI is executed by 2-parties, a client and a server, where both a client and a server compute jointly the intersection of their private sets and at the end only the client learns the intersection and the server learns nothing. From the scalable point of view, however, the number of parties are not limited to two. In this paper, we propose a scalable and flexible multiparty PSI (MPSI) for the first time: the data size of each party is independent to each other and the computational complexity is independent to the number of parties. We also propose d-and-over MPSI for the first time.