Secure Privacy-Preserving Association Rule Mining With Single Cloud Server

To preserve the privacy of data uploaded on the cloud, it is widely accepted to encrypt the data before uploading it. This leads to the challenge of data analysis, especially association rule mining while protecting data privacy. As one of the solutions, homomorphic encryption is presented allowing...

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Main Authors: Zhiyong Hong, Zhili Zhang, Pu Duan, Benyu Zhang, Baocang Wang, Wen Gao, Zhen Zhao
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9615206/
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author Zhiyong Hong
Zhili Zhang
Pu Duan
Benyu Zhang
Baocang Wang
Wen Gao
Zhen Zhao
author_facet Zhiyong Hong
Zhili Zhang
Pu Duan
Benyu Zhang
Baocang Wang
Wen Gao
Zhen Zhao
author_sort Zhiyong Hong
collection DOAJ
description To preserve the privacy of data uploaded on the cloud, it is widely accepted to encrypt the data before uploading it. This leads to the challenge of data analysis, especially association rule mining while protecting data privacy. As one of the solutions, homomorphic encryption is presented allowing encrypted data processing without decryption. In particular, the twin-cloud structure is frequently applied in the privacy-preserving association rule mining schemes based on asymmetric homomorphic encryption, which contradicts the reality that most of the practical applications applied the single cloud server. However, the existing related single cloud server schemes suffer from privacy leakage problems. To fill this gap in the literature, in this paper, we first present a universal secure multiplication protocol with the single cloud server using the garbled circuit and additive homomorphic encryption. Based on this multiplication protocol, we construct the inner product protocol, comparison protocol, frequent itemset protocol, and the final association rule mining protocol that is secure against privacy leakage. Finally, we give the theoretical security analysis of the proposed protocols and show its performance analysis.
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spelling doaj.art-7218ee7294f04f34a816789e243b09da2022-12-21T20:21:25ZengIEEEIEEE Access2169-35362021-01-01916509016510210.1109/ACCESS.2021.31285269615206Secure Privacy-Preserving Association Rule Mining With Single Cloud ServerZhiyong Hong0Zhili Zhang1https://orcid.org/0000-0002-6709-9506Pu Duan2Benyu Zhang3Baocang Wang4https://orcid.org/0000-0002-2554-4464Wen Gao5Zhen Zhao6https://orcid.org/0000-0003-2654-624XFacility of Intelligence Manufacture, Wuyi University, Jiangmen, ChinaSchool of Information Engineering, Xuchang University, Xuchang, ChinaAnt Group, Hangzhou, ChinaAnt Group, Hangzhou, ChinaState Key Laboratory of Integrated Service Networks, Xidian University, Xi’an, ChinaSchool of Cyberspace Security, Xi’an University of Posts and Telecommunications, Xi’an, ChinaState Key Laboratory of Integrated Service Networks, Xidian University, Xi’an, ChinaTo preserve the privacy of data uploaded on the cloud, it is widely accepted to encrypt the data before uploading it. This leads to the challenge of data analysis, especially association rule mining while protecting data privacy. As one of the solutions, homomorphic encryption is presented allowing encrypted data processing without decryption. In particular, the twin-cloud structure is frequently applied in the privacy-preserving association rule mining schemes based on asymmetric homomorphic encryption, which contradicts the reality that most of the practical applications applied the single cloud server. However, the existing related single cloud server schemes suffer from privacy leakage problems. To fill this gap in the literature, in this paper, we first present a universal secure multiplication protocol with the single cloud server using the garbled circuit and additive homomorphic encryption. Based on this multiplication protocol, we construct the inner product protocol, comparison protocol, frequent itemset protocol, and the final association rule mining protocol that is secure against privacy leakage. Finally, we give the theoretical security analysis of the proposed protocols and show its performance analysis.https://ieeexplore.ieee.org/document/9615206/Privacy-preserving association rule miningsingle cloud servergarbled circuithomomorphic encryption
spellingShingle Zhiyong Hong
Zhili Zhang
Pu Duan
Benyu Zhang
Baocang Wang
Wen Gao
Zhen Zhao
Secure Privacy-Preserving Association Rule Mining With Single Cloud Server
IEEE Access
Privacy-preserving association rule mining
single cloud server
garbled circuit
homomorphic encryption
title Secure Privacy-Preserving Association Rule Mining With Single Cloud Server
title_full Secure Privacy-Preserving Association Rule Mining With Single Cloud Server
title_fullStr Secure Privacy-Preserving Association Rule Mining With Single Cloud Server
title_full_unstemmed Secure Privacy-Preserving Association Rule Mining With Single Cloud Server
title_short Secure Privacy-Preserving Association Rule Mining With Single Cloud Server
title_sort secure privacy preserving association rule mining with single cloud server
topic Privacy-preserving association rule mining
single cloud server
garbled circuit
homomorphic encryption
url https://ieeexplore.ieee.org/document/9615206/
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