A Privacy-Preserving Multi-Keyword Ranked Search Over Encrypted Data in Hybrid Clouds
With the rapid development of cloud computing services, more and more individuals and enterprises prefer to outsource their data or computing to clouds. In order to preserve data privacy, the data should be encrypted before outsourcing and it is a challenge to perform searches over encrypted data. I...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8946623/ |
| _version_ | 1818323755419566080 |
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| author | Hua Dai Yan Ji Geng Yang Haiping Huang Xun Yi |
| author_facet | Hua Dai Yan Ji Geng Yang Haiping Huang Xun Yi |
| author_sort | Hua Dai |
| collection | DOAJ |
| description | With the rapid development of cloud computing services, more and more individuals and enterprises prefer to outsource their data or computing to clouds. In order to preserve data privacy, the data should be encrypted before outsourcing and it is a challenge to perform searches over encrypted data. In this paper, we propose a privacy-preserving multi-keyword ranked search scheme over encrypted data in hybrid clouds, which is denoted as MRSE-HC. The keyword dictionary of documents is clustered into balanced partitions by a bisecting $k$ -means clustering based keyword partition algorithm. According to the partitions, the keyword partition based bit vectors are adopted for documents and queries which are utilized as the index of searches. The private cloud filters out the candidate documents by the keyword partition based bit vectors, and then the public cloud uses the trapdoor to determine the result in the candidates. On the basis of the MRSE-HC scheme, an enhancement scheme EMRSE-HC is proposed, which adds complete binary pruning tree to further improve search efficiency. The security analysis and performance evaluation show that MRSE-HC and EMRSE-HC are privacy-preserving multi-keyword ranked search schemes for hybrid clouds and outperforms the existing scheme FMRS in terms of search efficiency. |
| first_indexed | 2024-12-13T11:17:44Z |
| format | Article |
| id | doaj.art-a7952478009e4c1eb36eb3b46e2ccb02 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-13T11:17:44Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-a7952478009e4c1eb36eb3b46e2ccb022022-12-21T23:48:34ZengIEEEIEEE Access2169-35362020-01-0184895490710.1109/ACCESS.2019.29630968946623A Privacy-Preserving Multi-Keyword Ranked Search Over Encrypted Data in Hybrid CloudsHua Dai0https://orcid.org/0000-0003-2465-8977Yan Ji1https://orcid.org/0000-0003-2120-7476Geng Yang2https://orcid.org/0000-0001-7740-2401Haiping Huang3https://orcid.org/0000-0002-4392-3599Xun Yi4https://orcid.org/0000-0001-7351-5724Nanjing University of Post and Telecommunication, Nanjing, ChinaNanjing University of Post and Telecommunication, Nanjing, ChinaNanjing University of Post and Telecommunication, Nanjing, ChinaNanjing University of Post and Telecommunication, Nanjing, ChinaRoyal Melbourne Institute of Technology University, Melbourne, VIC, AustraliaWith the rapid development of cloud computing services, more and more individuals and enterprises prefer to outsource their data or computing to clouds. In order to preserve data privacy, the data should be encrypted before outsourcing and it is a challenge to perform searches over encrypted data. In this paper, we propose a privacy-preserving multi-keyword ranked search scheme over encrypted data in hybrid clouds, which is denoted as MRSE-HC. The keyword dictionary of documents is clustered into balanced partitions by a bisecting $k$ -means clustering based keyword partition algorithm. According to the partitions, the keyword partition based bit vectors are adopted for documents and queries which are utilized as the index of searches. The private cloud filters out the candidate documents by the keyword partition based bit vectors, and then the public cloud uses the trapdoor to determine the result in the candidates. On the basis of the MRSE-HC scheme, an enhancement scheme EMRSE-HC is proposed, which adds complete binary pruning tree to further improve search efficiency. The security analysis and performance evaluation show that MRSE-HC and EMRSE-HC are privacy-preserving multi-keyword ranked search schemes for hybrid clouds and outperforms the existing scheme FMRS in terms of search efficiency.https://ieeexplore.ieee.org/document/8946623/Hybrid cloudmulti-keyword ranked searchprivacy-preservingsearchable encryption |
| spellingShingle | Hua Dai Yan Ji Geng Yang Haiping Huang Xun Yi A Privacy-Preserving Multi-Keyword Ranked Search Over Encrypted Data in Hybrid Clouds IEEE Access Hybrid cloud multi-keyword ranked search privacy-preserving searchable encryption |
| title | A Privacy-Preserving Multi-Keyword Ranked Search Over Encrypted Data in Hybrid Clouds |
| title_full | A Privacy-Preserving Multi-Keyword Ranked Search Over Encrypted Data in Hybrid Clouds |
| title_fullStr | A Privacy-Preserving Multi-Keyword Ranked Search Over Encrypted Data in Hybrid Clouds |
| title_full_unstemmed | A Privacy-Preserving Multi-Keyword Ranked Search Over Encrypted Data in Hybrid Clouds |
| title_short | A Privacy-Preserving Multi-Keyword Ranked Search Over Encrypted Data in Hybrid Clouds |
| title_sort | privacy preserving multi keyword ranked search over encrypted data in hybrid clouds |
| topic | Hybrid cloud multi-keyword ranked search privacy-preserving searchable encryption |
| url | https://ieeexplore.ieee.org/document/8946623/ |
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