Protecting moving trajectories with dummies

Tun Hao You*, Wen-Chih Peng, Wang Chien Lee

*Corresponding author for this work

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

101 Scopus citations

Abstract

Dummy-based anonymization techniques for protecting location privacy of mobile users have been proposed in the literature. By generating dummies that move in human-like trajectories, [8] shows that location privacy of mobile users can be preserved. However, by monitoring long-term movement patterns of users, the trajectories of mobile users can still be exposed. We argue that, once the trajectory of a user is identified, locations of the user is exposed. Thus, it's critical to protect the moving trajectories of mobile users in order to preserve user location privacy. We propose two schemes that generate consistent movement patterns in a long run. Guided by three parameters in user specified privacy profile, namely, short-term disclosure, long-term disclosure and distance deviation, the proposed schemes derive movement trajectories for dummies. A preliminary performance study shows that our approach is more effective than existing work in protecting moving trajectories of mobile users and their location privacy.

Original languageEnglish
Title of host publicationProceedings - 8th International Conference on Mobile Data Management, MDM 2007
Pages278-282
Number of pages5
DOIs
StatePublished - 1 Dec 2007
Event8th International Conference on Mobile Data Management, MDM 2007 - Mannheim, Germany
Duration: 7 May 200711 May 2007

Publication series

NameProceedings - IEEE International Conference on Mobile Data Management
ISSN (Print)1551-6245

Conference

Conference8th International Conference on Mobile Data Management, MDM 2007
CountryGermany
CityMannheim
Period7/05/0711/05/07

Keywords

  • Location privacy
  • Location-based services
  • User movement patterns

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