Privacy-Preserving Ad-Hoc Equi-Join on Outsourced Data

In IT outsourcing, a user may delegate the data storage and query processing functions to a third-party server that is not completely trusted. This gives rise to the need to safeguard the privacy of the database as well as the user queries over it. In this article, we address the problem of running...

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Main Authors: PANG, Hwee Hwa, DING, Xuhua
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Language:English
Published: Institutional Knowledge at Singapore Management University 2014
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Online Access:https://ink.library.smu.edu.sg/sis_research/2257
https://ink.library.smu.edu.sg/context/sis_research/article/3257/viewcontent/Privacy_Preserving_Ad_Hoc_Equi_Join_on_Outsourced_Data__edited_.pdf
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spelling sg-smu-ink.sis_research-32572018-07-13T03:52:20Z Privacy-Preserving Ad-Hoc Equi-Join on Outsourced Data PANG, Hwee Hwa DING, Xuhua In IT outsourcing, a user may delegate the data storage and query processing functions to a third-party server that is not completely trusted. This gives rise to the need to safeguard the privacy of the database as well as the user queries over it. In this article, we address the problem of running ad hoc equi-join queries directly on encrypted data in such a setting. Our contribution is the first solution that achieves constant complexity per pair of records that are evaluated for the join. After formalizing the privacy requirements pertaining to the database and user queries, we introduce a cryptographic construct for securely joining records across relations. The construct protects the database with a strong encryption scheme. Moreover, information disclosure after executing an equi-join is kept to the minimum—that two input records combine to form an output record if and only if they share common join attribute values. There is no disclosure on records that are not part of the join result. Building on this construct, we then present join algorithms that optimize the join execution by eliminating the need to match every record pair from the input relations. We provide a detailed analysis of the cost of the algorithms and confirm the analysis through extensive experiments with both synthetic and benchmark workloads. Through this evaluation, we tease out useful insights on how to configure the join algorithms to deliver acceptable execution time in practice. 2014-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/2257 info:doi/10.1145/2629501 https://ink.library.smu.edu.sg/context/sis_research/article/3257/viewcontent/Privacy_Preserving_Ad_Hoc_Equi_Join_on_Outsourced_Data__edited_.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 Information Security
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Information Security
spellingShingle Information Security
PANG, Hwee Hwa
DING, Xuhua
Privacy-Preserving Ad-Hoc Equi-Join on Outsourced Data
description In IT outsourcing, a user may delegate the data storage and query processing functions to a third-party server that is not completely trusted. This gives rise to the need to safeguard the privacy of the database as well as the user queries over it. In this article, we address the problem of running ad hoc equi-join queries directly on encrypted data in such a setting. Our contribution is the first solution that achieves constant complexity per pair of records that are evaluated for the join. After formalizing the privacy requirements pertaining to the database and user queries, we introduce a cryptographic construct for securely joining records across relations. The construct protects the database with a strong encryption scheme. Moreover, information disclosure after executing an equi-join is kept to the minimum—that two input records combine to form an output record if and only if they share common join attribute values. There is no disclosure on records that are not part of the join result. Building on this construct, we then present join algorithms that optimize the join execution by eliminating the need to match every record pair from the input relations. We provide a detailed analysis of the cost of the algorithms and confirm the analysis through extensive experiments with both synthetic and benchmark workloads. Through this evaluation, we tease out useful insights on how to configure the join algorithms to deliver acceptable execution time in practice.
format text
author PANG, Hwee Hwa
DING, Xuhua
author_facet PANG, Hwee Hwa
DING, Xuhua
author_sort PANG, Hwee Hwa
title Privacy-Preserving Ad-Hoc Equi-Join on Outsourced Data
title_short Privacy-Preserving Ad-Hoc Equi-Join on Outsourced Data
title_full Privacy-Preserving Ad-Hoc Equi-Join on Outsourced Data
title_fullStr Privacy-Preserving Ad-Hoc Equi-Join on Outsourced Data
title_full_unstemmed Privacy-Preserving Ad-Hoc Equi-Join on Outsourced Data
title_sort privacy-preserving ad-hoc equi-join on outsourced data
publisher Institutional Knowledge at Singapore Management University
publishDate 2014
url https://ink.library.smu.edu.sg/sis_research/2257
https://ink.library.smu.edu.sg/context/sis_research/article/3257/viewcontent/Privacy_Preserving_Ad_Hoc_Equi_Join_on_Outsourced_Data__edited_.pdf
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