Achieving k-anonymity in privacy-aware location-based services

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

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

427 Scopus citations


Location-Based Service (LBS) has become a vital part of our daily life. While enjoying the convenience provided by LBS, users may lose privacy since the untrusted LBS server has all the information about users in LBS and it may track them in various ways or release their personal data to third parties. To address the privacy issue, we propose a Dummy-Location Selection (DLS) algorithm to achieve k-anonymity for users in LBS. Different from existing approaches, the DLS algorithm carefully selects dummy locations considering that side information may be exploited by adversaries. We first choose these dummy locations based on the entropy metric, and then propose an enhanced-DLS algorithm, to make sure that the selected dummy locations are spread as far as possible. Evaluation results show that the proposed DLS algorithm can significantly improve the privacy level in terms of entropy. The enhanced-DLS algorithm can enlarge the cloaking region while keeping similar privacy level as the DLS algorithm.

Original languageEnglish (US)
Title of host publicationIEEE INFOCOM 2014 - IEEE Conference on Computer Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages9
ISBN (Print)9781479933600
StatePublished - 2014
Event33rd IEEE Conference on Computer Communications, IEEE INFOCOM 2014 - Toronto, ON, Canada
Duration: Apr 27 2014May 2 2014

Publication series

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


Other33rd IEEE Conference on Computer Communications, IEEE INFOCOM 2014
CityToronto, ON

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Electrical and Electronic Engineering


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