Title

Private Set Intersection with Authorization over Outsourced Encrypted Datasets

Publication Name

IEEE Transactions on Information Forensics and Security

Abstract

Thanks to its convenience and cost-savings feature, cloud computing ushers a new era. Yet its security and privacy issues must not be neglected. Private set intersection (PSI) is useful and important in many cloud computing applications, such as document similarity, genetic paternity and data mining. The cloud server performs intersection operations on two outsourced encrypted datasets of data owners. In the existing protocols, however, data owners cannot decide whether to use all or part of their encrypted data to compute the intersection, nor can they specify whom to compare with. In this paper, we introduce an enhanced notion of outsourced PSI, called authorized PSI (APSI), which supports flexible authorization and cross-type authorized comparison of datasets. To demonstrate this notion, we propose a concrete APSI protocol, and prove it to be secure in the random oracle model based on simple number-theoretic assumptions. Experimental results show that our APSI protocol has performance comparable with existing related outsourced PSI protocols.

Open Access Status

This publication is not available as open access

Volume

16

Article Number

9500119

First Page

4050

Last Page

4062

Funding Number

2019B030302008

Funding Sponsor

National Natural Science Foundation of China

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Link to publisher version (DOI)

http://dx.doi.org/10.1109/TIFS.2021.3101059