A communication-efficient private matching scheme in Client-Server model

Mu-En Wu, Shih-Ying Chang, Chi-Jen Lu, Hung-Min Sun

Abstract: In a Private Matching (PM) scheme, the client C has a dataset X of m elements, and the server S has a dataset Y of n elements. The client C can learn the set intersection X∩Y without leaking any information to the server S. Previously, the most efficient PM scheme requires communication of complexity O∼(m+n), which increases linearly with n. This may not be efficient enough in Client–Server models because the server’s dataset Y is usually large. In this paper, we propose a PM scheme based on Oblivious Transfer (OT) and universal hash function. Our scheme requires communication of complexity O∼(m·log2n). Thus, our scheme is especially suitable for Client–Server models. We show that our scheme becomes more efficient when log2(mn)1+Δ=O∼nm for security parameter Δ>0. However, utilizing the universal hash function would cause a mismatch issue which affects the accuracy of the PM scheme. In addition, it leaks the server’s information. Therefore, we define approximate PM by relaxing the definition of PM; it is proved to be almost as secure as a PM scheme in a Client–Server model with proper configurations.