Efficient multiparty private set intersection protocol based on function secret sharing

Abstract

Multiparty Private Set Intersection (MPSI) protocols afford protection of set data privacy but concurrently introduce substantial computational overhead. While this overhead is tolerable when dealing with modest-sized sets and a limited number of participants, it becomes burdensome as set cardinality and participant count escalate. Consequently, these protocols exhibit constraints regarding set size or participant quantity, thereby diminishing their practical feasibility in scenarios involving extensive sets and numerous participants. To address these challenges, this paper introduces a novel MPSI protocol based on function secret sharing. Our protocol effectively computes the intersection elements while ensuring the confidentiality of set data, rendering it well-suited for scenarios characterized by a considerable number of candidates and large-scale sets. Extensive testing and comparative analysis against other MPSI protocols are conducted to evaluate the proposed protocol's performance and effectiveness.