Communication Efficient Multiparty Private Set Intersection from Multi-Point Sequential OPRF

2025-05-31

AI Summary

To address the load concentration in star-topology multi-party private set intersection (MPSI) and the high communication overhead in mesh-topology variants, this paper proposes the first efficient ring-topology-based MPSI protocol. Our method introduces the first multi-point sequentially oblivious pseudorandom function (MP-SOPRF), integrated with ring-structured communication orchestration and security grounded in the Hamming correlation robustness assumption. The resulting protocol achieves security against semi-honest adversaries while minimizing computational and communication costs. Theoretical analysis and empirical evaluation demonstrate that, compared to the state-of-the-art, our protocol reduces total communication by 74.8% and improves computational efficiency by 6%–287%, striking a superior balance among security, scalability, and practicality.

Technology Category

• Search and Optimization: Distributed Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Machine Learning: Privacy

Application Category

• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines

Abstract

Multiparty private set intersection (MPSI) allows multiple participants to compute the intersection of their locally owned data sets without revealing them. MPSI protocols can be categorized based on the network topology of nodes, with the star, mesh, and ring topologies being the primary types, respectively. Given that star and mesh topologies dominate current implementations, most existing MPSI protocols are based on these two topologies. However, star-topology MPSI protocols suffer from high leader node load, while mesh topology protocols suffer from high communication complexity and overhead. In this paper, we first propose a multi-point sequential oblivious pseudorandom function (MP-SOPRF) in a multi-party setting. Based on MP-SOPRF, we then develop an MPSI protocol with a ring topology, addressing the challenges of communication and computational overhead in existing protocols. We prove that our MPSI protocol is semi-honest secure under the Hamming correlation robustness assumption. Our experiments demonstrate that our MPSI protocol outperforms state-of-the-art protocols, achieving a reduction of 74.8% in communication and a 6% to 287% improvement in computational efficiency.

Problem

• Reduces leader node load in star-topology MPSI protocols
• Lowers communication complexity in mesh-topology MPSI protocols
• Improves efficiency in multiparty private set intersection

Innovation

• Proposes multi-point sequential OPRF (MP-SOPRF)
• Develops ring-topology MPSI protocol
• Reduces communication and computational overhead