Ensuring privacy and security for LBS through trajectory partitioning

Heechang Shin, Jaideep Vaidya, Vijayalakshmi Atluri, Sungyong Choi

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

23 Scopus citations

Abstract

The concept of location κ-anonymity has been proposed to address the privacy issue of location based services (LBS). Under this notion of anonymity, the adversary only has the knowledge that the LBS request originates from a region containing at least κ people, and therefore cannot individually distinguish the requestor. However, new types of LBS services such as continuous nearest neighbor searches require the knowledge of the user's trajectory, which can lead to a privacy breach. The longer the adversary can track the user's trajectory, the stronger the possibility that the user's sensitive information is revealed. To alleviate this problem, we propose algorithms to optimally partition a continuous request into multiple LBS requests with shorter trajectories. This results in increased privacy due to the unlinking of different requests over time and has the added benefit of improving the overall quality of service since the anonymized regions are now smaller. Our experimental results show that significant privacy and QoS benefits can be achieved with nominal computational overhead.

Original languageEnglish (US)
Title of host publicationMDM2010 - 11th International Conference on Mobile Data Management
Pages224-226
Number of pages3
DOIs
StatePublished - 2010
Event11th IEEE International Conference on Mobile Data Management, MDM 2010 - Kansas City, MO, United States
Duration: May 23 2010May 26 2010

Publication series

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

Other

Other11th IEEE International Conference on Mobile Data Management, MDM 2010
CountryUnited States
CityKansas City, MO
Period5/23/105/26/10

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Keywords

  • Anonymization
  • LBS
  • Privacy
  • Trajectory

Fingerprint Dive into the research topics of 'Ensuring privacy and security for LBS through trajectory partitioning'. Together they form a unique fingerprint.

Cite this