Authenticated spatio-textual similarity joins in untrusted cloud environments

Han Yan, Xiang Cheng, Sen Su, Qiying Zhang, Jianliang XU

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

1 Citation (Scopus)

Abstract

A spatio-textual similarity join searches a spatiotextual data collection and reports the object pairs that satisfy the specified spatial distance threshold and textual similarity threshold. However, when the data owner outsources the join computations to a third-party cloud service provider, the service provider may send incomplete or incorrect join results to the data owner. In this paper, we propose a pairwise authentication scheme, a cluster based scheme and an order and bound based scheme to authenticate the results of spatiotextual similarity joins. Extensive experiments on a real-world dataset verify the effectiveness and efficiency of our proposed schemes in terms of various performance metrics.

Original languageEnglish
Title of host publicationProceedings - 22nd IEEE International Conference on Parallel and Distributed Systems, ICPADS 2016
EditorsXiaofei Liao, Robert Lovas, Xipeng Shen, Ran Zheng
PublisherIEEE Computer Society
Pages685-694
Number of pages10
ISBN (Electronic)9781509044573
DOIs
Publication statusPublished - 2 Jul 2016
Event22nd IEEE International Conference on Parallel and Distributed Systems, ICPADS 2016 - Wuhan, Hubei, China
Duration: 13 Dec 201616 Dec 2016

Publication series

NameProceedings of the International Conference on Parallel and Distributed Systems - ICPADS
Volume0
ISSN (Print)1521-9097

Conference

Conference22nd IEEE International Conference on Parallel and Distributed Systems, ICPADS 2016
Country/TerritoryChina
CityWuhan, Hubei
Period13/12/1616/12/16

Scopus Subject Areas

  • Hardware and Architecture

User-Defined Keywords

  • Cloud computing
  • Computation outsourcing
  • Location-based services
  • Query authentication
  • Spatio-textual similarity joins

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