Privacy Preserving Inner Product of Vectors in Cloud Computing
The problem of privacy preserving inner product of vectors has been widely studied. Much work has been done on the scenario of two parties involved in the computation. In this paper, we consider the scenario where three parties are involved in the computing process of cloud computing. We propose a n...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi - SAGE Publishing
2014-05-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2014/537252 |
| _version_ | 1797726977323433984 |
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| author | Gang Sheng Tao Wen Quan Guo Ying Yin |
| author_facet | Gang Sheng Tao Wen Quan Guo Ying Yin |
| author_sort | Gang Sheng |
| collection | DOAJ |
| description | The problem of privacy preserving inner product of vectors has been widely studied. Much work has been done on the scenario of two parties involved in the computation. In this paper, we consider the scenario where three parties are involved in the computing process of cloud computing. We propose a new privacy preserving scheme for inner product of two vectors in the cloud and give the correctness analysis and performance analysis for the scheme. The proposed scheme is based on homomorphic encryption, and the security can be guaranteed. Experiments show the efficiency of the scheme. |
| first_indexed | 2024-03-12T10:53:13Z |
| format | Article |
| id | doaj.art-1f5589a0cd0442198d51553768d98719 |
| institution | Directory Open Access Journal |
| issn | 1550-1477 |
| language | English |
| last_indexed | 2024-03-12T10:53:13Z |
| publishDate | 2014-05-01 |
| publisher | Hindawi - SAGE Publishing |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj.art-1f5589a0cd0442198d51553768d987192023-09-02T06:40:05ZengHindawi - SAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772014-05-011010.1155/2014/537252537252Privacy Preserving Inner Product of Vectors in Cloud ComputingGang Sheng0Tao Wen1Quan Guo2Ying Yin3 Software Center, Northeastern University, Shenyang 110819, China Software Center, Northeastern University, Shenyang 110819, China Department of Computer Science and Technology, Dalian Neusoft University of Information, Dalian 116023, China College of Information Science and Engineering, Northeastern University, Shenyang 110819, ChinaThe problem of privacy preserving inner product of vectors has been widely studied. Much work has been done on the scenario of two parties involved in the computation. In this paper, we consider the scenario where three parties are involved in the computing process of cloud computing. We propose a new privacy preserving scheme for inner product of two vectors in the cloud and give the correctness analysis and performance analysis for the scheme. The proposed scheme is based on homomorphic encryption, and the security can be guaranteed. Experiments show the efficiency of the scheme.https://doi.org/10.1155/2014/537252 |
| spellingShingle | Gang Sheng Tao Wen Quan Guo Ying Yin Privacy Preserving Inner Product of Vectors in Cloud Computing International Journal of Distributed Sensor Networks |
| title | Privacy Preserving Inner Product of Vectors in Cloud Computing |
| title_full | Privacy Preserving Inner Product of Vectors in Cloud Computing |
| title_fullStr | Privacy Preserving Inner Product of Vectors in Cloud Computing |
| title_full_unstemmed | Privacy Preserving Inner Product of Vectors in Cloud Computing |
| title_short | Privacy Preserving Inner Product of Vectors in Cloud Computing |
| title_sort | privacy preserving inner product of vectors in cloud computing |
| url | https://doi.org/10.1155/2014/537252 |
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