Authenticating location-based services without compromising location privacy

Haibo HU*, Jianliang XU, Qian Chen, Ziwei Yang

*Corresponding author for this work

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

58 Citations (Scopus)

Abstract

The popularity of mobile social networking services (mSNSs) is propelling more and more businesses, especially those in retailing and marketing, into mobile and location-based forms. To address the trust issue, the service providers are expected to deliver their location-based services in an authenticatable manner, so that the correctness of the service results can be verified by the client. However, existing works on query authentication cannot preserve the privacy of the data being queried, which are sensitive user locations when it comes to location-based services and mSNSs. In this paper, we address this challenging problem by proposing a comprehensive solution that preserves unconditional location privacy when authenticating range queries. Three authentication schemes for R-tree and grid-file index, together with two optimization techniques, are developed. Cost models, security analysis, and experimental results consistently show the effectiveness, reliability and robustness of the proposed schemes under various system settings and query workloads.

Original languageEnglish
Title of host publicationSIGMOD '12 - Proceedings of the International Conference on Management of Data
Pages301-312
Number of pages12
DOIs
Publication statusPublished - 2012
EventACM SIGMOD International Conference on Management of Data, SIGMOD 2012 - Scottsdale, AZ, United States
Duration: 21 May 201224 May 2012

Publication series

NameProceedings of the ACM SIGMOD International Conference on Management of Data
ISSN (Print)0730-8078

Conference

ConferenceACM SIGMOD International Conference on Management of Data, SIGMOD 2012
Country/TerritoryUnited States
CityScottsdale, AZ
Period21/05/1224/05/12

Scopus Subject Areas

  • Software
  • Information Systems

User-Defined Keywords

  • lbs
  • privacy-preserving
  • query authentication

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