CLPP: Context-aware location privacy protection for location-based social network

Hongli Zhang, Zhikai Xu, Zhigang Zhou, Jiantao Shi, Xiaojiang Du

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

12 Scopus citations

Abstract

Location-based social network (LBSN) has grown exponentially over the past several years. Given its high utility value, LBSN, however, has raised serious concerns about users' location privacy. Although users may avoid releasing geo-content in sensitive locations, this, however, does not necessarily prevent the adversary from inferring users' privacy through spatial-temporal correlations and historical information. In this paper, we introduce a new location privacy problem: context-aware location privacy protection (CLPP) problem where the privacy requirements of users are not constant and isolated. We propose a novel metric to quantify the privacy risks. Then the CLPP is formalized as how to accurately and efficiently evaluate whether the users' published geo-content meet the user's privacy requirement. To achieve online evaluating, we design two novel algorithms to calculate the correlation between the locations. Eventually, our experimental results demonstrate the validity and practicality of the proposed strategy.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Communications, ICC 2015
Pages1164-1169
Number of pages6
ISBN (Electronic)9781467364324
DOIs
StatePublished - 9 Sep 2015
EventIEEE International Conference on Communications, ICC 2015 - London, United Kingdom
Duration: 8 Jun 201512 Jun 2015

Publication series

NameIEEE International Conference on Communications
Volume2015-September
ISSN (Print)1550-3607

Conference

ConferenceIEEE International Conference on Communications, ICC 2015
Country/TerritoryUnited Kingdom
CityLondon
Period8/06/1512/06/15

Keywords

  • inference attack
  • location privacy
  • location-based social network
  • privacy preserving

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