Secure Privacy-Preserving Association Rule Mining With Single Cloud Server

Zhiyong Hong,Zhen Zhao,Pu Duan,Baocang Wang,Zhili Zhang,Wen Gao,Benyu Zhang

doi:10.1109/access.2021.3128526

Abstract

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.

Highlights

I N the information era, people’s life is transferred into data and stored on the network, such as shopping preference, traffic line, and hobbies
OUR CONTRIBUTION To remove the strong assumption that two cloud servers will not collude with each other in the twin-cloud setting and fill the gap that the single-cloud setting always leads to privacy disclosure, we propose a secure privacy-preserving association rule mining scheme based on a single-cloudserver setting
By invoking the above multiplication protocol, we construct the following inner product protocol, where the data miner (DM) sends the ciphertext of a mining query, [x] = ([x1], [x2], · · ·, [xl]), to the cloud service provider (CSP) who owns the ciphertext of a transaction record, [y] = ([y1], [y2], · · ·, [yl])

Summary

INTRODUCTION

I N the information era, people’s life is transferred into data and stored on the network, such as shopping preference, traffic line, and hobbies. Yi et al [23] proposed a privacypreserving association rule mining protocol based on Elgamal homomorphic encryption algorithm In their protocol, a data miner can outsource all computations to cloud servers, and data owners only perform some encryption operations. Liu et al [29] proposed a privacy-preserving association rule mining scheme for outsourced cloud data in a multi-key environment based on the BCP homomorphic encryption [30], [31]. B. OUR CONTRIBUTION To remove the strong assumption that two cloud servers will not collude with each other in the twin-cloud setting and fill the gap that the single-cloud setting always leads to privacy disclosure, we propose a secure privacy-preserving association rule mining scheme based on a single-cloudserver setting.

PRELIMINARIES

ASSOCIATION RULE MINING

ASSOCIATION RULE MINING PROTOCOL

SECURITY ANALYSIS

THEORETICAL ANALYSIS Encryption overhead

CONCLUSION