Efficient and privacy-preserving outsourced calculation of rational numbers
In this paper, we propose a framework for efficient and privacy-preserving outsourced calculation of rational numbers, which we refer to as POCR. Using POCR, a user can securely outsource the storing and processing of rational numbers to a cloud server without compromising the security of the (origi...
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Main Authors: | , , , , |
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Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2018
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Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/4116 https://ink.library.smu.edu.sg/context/sis_research/article/5119/viewcontent/Privacy_Preserving_Rational_Numbers_2018_afv.pdf |
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Institution: | Singapore Management University |
Language: | English |
Summary: | In this paper, we propose a framework for efficient and privacy-preserving outsourced calculation of rational numbers, which we refer to as POCR. Using POCR, a user can securely outsource the storing and processing of rational numbers to a cloud server without compromising the security of the (original) data and the computed results. We present the system architecture of POCR and the associated toolkits required in the privacy preserving calculation of integers and rational numbers to ensure that commonly used outsourced operations can be handled on-the-fly. We then prove that the proposed POCR achieves the goal of secure integer and rational number calculation without resulting in privacy leakage to unauthorized parties, and demonstrate the utility and the efficiency of POCR using simulations. |
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