An efficient privacy-preserving outsourced calculation toolkit with multiple keys

In this paper, we propose a toolkit for efficient and privacy-preserving outsourced calculation under multiple encrypted keys (EPOM). Using EPOM, a large scale of users can securely outsource their data to a cloud server for storage. Moreover, encrypted data belonging to multiple users can be proces...

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Main Authors: LIU, Ximeng, DENG, Robert H., CHOO, Kim-Kwang Raymond, WENG, Jian
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2016
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Online Access:https://ink.library.smu.edu.sg/sis_research/3501
https://ink.library.smu.edu.sg/context/sis_research/article/4502/viewcontent/EfficientPrivacyPreservingOutsourcedCal_ITIFS_2016.pdf
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-45022019-06-06T01:53:13Z An efficient privacy-preserving outsourced calculation toolkit with multiple keys LIU, Ximeng DENG, Robert H. CHOO, Kim-Kwang Raymond WENG, Jian In this paper, we propose a toolkit for efficient and privacy-preserving outsourced calculation under multiple encrypted keys (EPOM). Using EPOM, a large scale of users can securely outsource their data to a cloud server for storage. Moreover, encrypted data belonging to multiple users can be processed without compromising on the security of the individual user's (original) data and the final computed results. To reduce the associated key management cost and private key exposure risk in EPOM, we present a distributed two-trapdoor public-key cryptosystem, the core cryptographic primitive. We also present the toolkit to ensure that the commonly used integer operations can be securely handled across different encrypted domains. We then prove that the proposed EPOM achieves the goal of secure integer number processing without resulting in privacy leakage of data to unauthorized parties. Last, we demonstrate the utility and the efficiency of EPOM using simulations. 2016-11-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/3501 info:doi/10.1109/TIFS.2016.2573770 https://ink.library.smu.edu.sg/context/sis_research/article/4502/viewcontent/EfficientPrivacyPreservingOutsourcedCal_ITIFS_2016.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Privacy-preserving homomorphic encryption outsourced computation multiple keys Computer Sciences Information Security
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Privacy-preserving
homomorphic encryption
outsourced computation
multiple keys
Computer Sciences
Information Security
spellingShingle Privacy-preserving
homomorphic encryption
outsourced computation
multiple keys
Computer Sciences
Information Security
LIU, Ximeng
DENG, Robert H.
CHOO, Kim-Kwang Raymond
WENG, Jian
An efficient privacy-preserving outsourced calculation toolkit with multiple keys
description In this paper, we propose a toolkit for efficient and privacy-preserving outsourced calculation under multiple encrypted keys (EPOM). Using EPOM, a large scale of users can securely outsource their data to a cloud server for storage. Moreover, encrypted data belonging to multiple users can be processed without compromising on the security of the individual user's (original) data and the final computed results. To reduce the associated key management cost and private key exposure risk in EPOM, we present a distributed two-trapdoor public-key cryptosystem, the core cryptographic primitive. We also present the toolkit to ensure that the commonly used integer operations can be securely handled across different encrypted domains. We then prove that the proposed EPOM achieves the goal of secure integer number processing without resulting in privacy leakage of data to unauthorized parties. Last, we demonstrate the utility and the efficiency of EPOM using simulations.
format text
author LIU, Ximeng
DENG, Robert H.
CHOO, Kim-Kwang Raymond
WENG, Jian
author_facet LIU, Ximeng
DENG, Robert H.
CHOO, Kim-Kwang Raymond
WENG, Jian
author_sort LIU, Ximeng
title An efficient privacy-preserving outsourced calculation toolkit with multiple keys
title_short An efficient privacy-preserving outsourced calculation toolkit with multiple keys
title_full An efficient privacy-preserving outsourced calculation toolkit with multiple keys
title_fullStr An efficient privacy-preserving outsourced calculation toolkit with multiple keys
title_full_unstemmed An efficient privacy-preserving outsourced calculation toolkit with multiple keys
title_sort efficient privacy-preserving outsourced calculation toolkit with multiple keys
publisher Institutional Knowledge at Singapore Management University
publishDate 2016
url https://ink.library.smu.edu.sg/sis_research/3501
https://ink.library.smu.edu.sg/context/sis_research/article/4502/viewcontent/EfficientPrivacyPreservingOutsourcedCal_ITIFS_2016.pdf
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