Enhancing privacy through caching in location-based services

Ben Niu, Qinghua Li, Xiaoyan Zhu, Guohong Cao, Hui Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

161 Scopus citations

Abstract

Privacy protection is critical for Location-Based Services (LBSs). In most previous solutions, users query service data from the untrusted LBS server when needed, and discard the data immediately after use. However, the data can be cached and reused to answer future queries. This prevents some queries from being sent to the LBS server and thus improves privacy. Although a few previous works recognize the usefulness of caching for better privacy, they use caching in a pretty straightforward way, and do not show the quantitative relation between caching and privacy. In this paper, we propose a caching-based solution to protect location privacy in LBSs, and rigorously explore how much caching can be used to improve privacy. Specifically, we propose an entropy-based privacy metric which for the first time incorporates the effect of caching on privacy. Then we design two novel caching-aware dummy selection algorithms which enhance location privacy through maximizing both the privacy of the current query and the dummies' contribution to cache. Evaluations show that our algorithms provide much better privacy than previous caching-oblivious and caching-aware solutions.

Original languageEnglish (US)
Title of host publication2015 IEEE Conference on Computer Communications, IEEE INFOCOM 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1017-1025
Number of pages9
ISBN (Electronic)9781479983810
DOIs
StatePublished - Aug 21 2015
Event34th IEEE Annual Conference on Computer Communications and Networks, IEEE INFOCOM 2015 - Hong Kong, Hong Kong
Duration: Apr 26 2015May 1 2015

Publication series

NameProceedings - IEEE INFOCOM
Volume26
ISSN (Print)0743-166X

Other

Other34th IEEE Annual Conference on Computer Communications and Networks, IEEE INFOCOM 2015
CountryHong Kong
CityHong Kong
Period4/26/155/1/15

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Electrical and Electronic Engineering

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