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Improved outsourced private set intersection protocol based on polynomial interpolation
Author(s) -
Yang Xiaoyuan,
Luo Xiaoshuang,
Wang Xu An,
Zhang Shuaiwei
Publication year - 2017
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.4329
Subject(s) - computer science , intersection (aeronautics) , protocol (science) , outsourcing , set operations , cloud computing , set (abstract data type) , cryptosystem , theoretical computer science , modular arithmetic , distributed computing , computer security , encryption , cryptography , operating system , programming language , engineering , medicine , political science , law , aerospace engineering , alternative medicine , pathology
Summary Private set intersection (PSI) protocols enable 2 parties to compute the intersection of their inputs without compromising anything about the datasets beyond the intersection. With the advent of cloud computing, outsourcing computation has been attracted wide range of attention from research community and applied widely in the industry. The cloud computing allows resources restrained devices to outsource their expensive computation to the cloud. Based on Abadi's O‐PSI, we present a variant of delegated private set intersection protocol secure in the semi‐honest model under RSA assumption, and we also give an efficient and secure outsourcing computation algorithm for RSA cryptosystem. Depending on this algorithm, we transform a variant of delegated private set intersection protocol into an improved outsourced one. It enables the clients only to perform simple modular multiplication for computing what they want during the execution of protocol. Besides, the variant of delegated protocol can be easily extended to multiple clients. Compared with the state of the art, our proposed protocol has great advantage in efficiency. We finally evaluate these protocols and prove their security in the semi‐honest model.