A Study on New EPC-MPSI for an Inputless External Party to Compute the Intersection of Multiple Private Datasets

Private set intersection (PSI) is a privacy-preserving scheme that computes the intersection of two datasets without leaking any other information. Additionally, there is multiparty private set intersection (MPSI) to extend the number of parties for computing the intersection of multiple private datasets. In the traditional PSI and MPSI studies, protocol parties input their private datasets, and one or all of them can compute the intersection. However, there are some scenarios where an inputless external party requires the intersection between private datasets of other parties. Thus, the external party PSI protocols have been recently studied for applications such as pandemic contact tracing, computing human genome information and evaluating policy effects. However, they are limited in applications because the external party can compute the intersection of two datasets. In this paper, we propose a new external party compute-MPSI (EPC-MPSI) protocols that allow an external party to compute the intersection of multiple datasets. We provide the extension of the number of parties and solve the limitation of prior external party PSI protocols. In addition, we analyze the correctness, security and the efficiency in terms of communication and computation costs compared to the prior traditional MPSI protocols.