Labeled Private Set Intersection From Distributed Point Function

IF 6.3 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Qi Liu;Xiaojie Guo;Kang Yang;Yu Yu
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引用次数: 0

Abstract

Private Set Intersection (PSI) allows two mutually distrusting parties to compute the intersection of their sets without revealing any additional information, and has found numerous applications. A part of applications require labeled PSI in the unbalanced setting, where a server holds a label for each item in a set that is much larger than the set held by a client, and the client obtains the intersection and the corresponding labels. In this paper, we present a new concretely efficient labeled PSI protocol in the unbalanced setting, without using computation-heavy homomorphic encryption. Our protocol is based on Distributed Point Function (DPF) with hardware acceleration from fixed-key AES-NI, and has communication complexity linear in the size of a small set of the client and sublinear in the size of a large set of the server. Our protocol exploits two Oblivious Pesudorandom Function (OPRF) protocols, based on Diffle-Hellman PRFs or block ciphers, to achieve a trade-off between computation and communication. Our implementation demonstrates that our protocol outperforms the previous labeled and unbalanced PSI protocols. In particular, for two sets with respective $2^{24}$ and 1 items, where each item has a 32-byte label, our protocol takes 1.19 seconds for an end-to-end performance, resulting in $26 \times $ improvement compared to the state-of-the-art protocol by Cong et al. (CCS 2021). In terms of the cost of the one-time initialization, we speed up the computations more than $325\times $ in the above comparison.
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来源期刊
IEEE Transactions on Information Forensics and Security
IEEE Transactions on Information Forensics and Security 工程技术-工程:电子与电气
CiteScore
14.40
自引率
7.40%
发文量
234
审稿时长
6.5 months
期刊介绍: The IEEE Transactions on Information Forensics and Security covers the sciences, technologies, and applications relating to information forensics, information security, biometrics, surveillance and systems applications that incorporate these features
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