Homomorphic Encryption Based Privacy Preservation Scheme for DBSCAN Clustering
In this paper, we propose a homomorphic encryption-based privacy protection scheme for DBSCAN clustering to reduce the risk of privacy leakage during data outsourcing computation. For the purpose of encrypting data in practical applications, we propose a variety of data preprocessing methods for dif...
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Format: | Article |
Language: | English |
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MDPI AG
2022-03-01
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Series: | Electronics |
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Online Access: | https://www.mdpi.com/2079-9292/11/7/1046 |
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author | Mingyang Wang Wenbin Zhao Kangda Cheng Zhilu Wu Jinlong Liu |
author_facet | Mingyang Wang Wenbin Zhao Kangda Cheng Zhilu Wu Jinlong Liu |
author_sort | Mingyang Wang |
collection | DOAJ |
description | In this paper, we propose a homomorphic encryption-based privacy protection scheme for DBSCAN clustering to reduce the risk of privacy leakage during data outsourcing computation. For the purpose of encrypting data in practical applications, we propose a variety of data preprocessing methods for different data accuracies. We also propose data preprocessing strategies based on different data precision and different computational overheads. In addition, we also design a protocol to implement the cipher text comparison function between users and cloud servers. Analysis of experimental results indicates that our proposed scheme has high clustering accuracy and can guarantee the privacy and security of the data. |
first_indexed | 2024-03-09T11:59:09Z |
format | Article |
id | doaj.art-f690240506d74715a828889f014bdd14 |
institution | Directory Open Access Journal |
issn | 2079-9292 |
language | English |
last_indexed | 2024-03-09T11:59:09Z |
publishDate | 2022-03-01 |
publisher | MDPI AG |
record_format | Article |
series | Electronics |
spelling | doaj.art-f690240506d74715a828889f014bdd142023-11-30T23:06:38ZengMDPI AGElectronics2079-92922022-03-01117104610.3390/electronics11071046Homomorphic Encryption Based Privacy Preservation Scheme for DBSCAN ClusteringMingyang Wang0Wenbin Zhao1Kangda Cheng2Zhilu Wu3Jinlong Liu4Southwest Institute of Electronic Technology of China, Chengdu 610036, ChinaSouthwest Institute of Electronic Technology of China, Chengdu 610036, ChinaSchool of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, ChinaSchool of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, ChinaSchool of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, ChinaIn this paper, we propose a homomorphic encryption-based privacy protection scheme for DBSCAN clustering to reduce the risk of privacy leakage during data outsourcing computation. For the purpose of encrypting data in practical applications, we propose a variety of data preprocessing methods for different data accuracies. We also propose data preprocessing strategies based on different data precision and different computational overheads. In addition, we also design a protocol to implement the cipher text comparison function between users and cloud servers. Analysis of experimental results indicates that our proposed scheme has high clustering accuracy and can guarantee the privacy and security of the data.https://www.mdpi.com/2079-9292/11/7/1046privacy protectiondensity clusteringhomomorphic encryption |
spellingShingle | Mingyang Wang Wenbin Zhao Kangda Cheng Zhilu Wu Jinlong Liu Homomorphic Encryption Based Privacy Preservation Scheme for DBSCAN Clustering Electronics privacy protection density clustering homomorphic encryption |
title | Homomorphic Encryption Based Privacy Preservation Scheme for DBSCAN Clustering |
title_full | Homomorphic Encryption Based Privacy Preservation Scheme for DBSCAN Clustering |
title_fullStr | Homomorphic Encryption Based Privacy Preservation Scheme for DBSCAN Clustering |
title_full_unstemmed | Homomorphic Encryption Based Privacy Preservation Scheme for DBSCAN Clustering |
title_short | Homomorphic Encryption Based Privacy Preservation Scheme for DBSCAN Clustering |
title_sort | homomorphic encryption based privacy preservation scheme for dbscan clustering |
topic | privacy protection density clustering homomorphic encryption |
url | https://www.mdpi.com/2079-9292/11/7/1046 |
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