Privacy-preserving outsourced calculation on floating point numbers

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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Bibliographic Details
Main Authors: LIU, Ximeng, DENG, Robert H., DING, Wenxiu, LU, Rongxing
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2016
Subjects:
Outsourcing
cloud computing
cryptographic protocols
data privacy
Computer Sciences
Information Security
Online Access: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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Institution: Singapore Management University
Language: English
Description
Summary: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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