Privacy-preserving outsourced calculation on floating point numbers
In this paper, we propose a framework for privacy-preserving outsourced calculation on floating point numbers (POCF). Using POCF, a user can securely outsource the storing and processing of floating point numbers to a cloud server without compromising on the security of the (original) data and the c...
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| Main Authors: | , , , |
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| 格式: | text |
| 語言: | English |
| 出版: |
Institutional Knowledge at Singapore Management University
2016
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| 主題: | |
| 在線閱讀: | https://ink.library.smu.edu.sg/sis_research/3889 https://ink.library.smu.edu.sg/context/sis_research/article/4891/viewcontent/PrivacyPreservingOutsourcedCalFPN_2016_IEEETIFS_afv.pdf |
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| 總結: | In this paper, we propose a framework for privacy-preserving outsourced calculation on floating point numbers (POCF). Using POCF, a user can securely outsource the storing and processing of floating point numbers to a cloud server without compromising on the security of the (original) data and the computed results. In particular, we first present privacy-preserving integer processing protocols for common integer operations. We then present an approach to outsourcing floating point numbers for storage in a privacy-preserving way, and securely processing commonly used floating point number operations on-the-fly. We prove that the proposed POCF achieves the goal of floating point number processing without privacy leakage to unauthorized parties, and demonstrate the utility and the efficiency of POCF using simulations. |
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