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GLPS: A Geohash-Based Location Privacy Protection Scheme.

Bin Liu1,2, Chunyong Zhang1, Liangwei Yao1

  • 1National Engineering Research Center for Disaster Backup and Recovery, Information Security Center, School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing 100876, China.

Entropy (Basel, Switzerland)
|December 23, 2023
PubMed
Summary

This study introduces GLPS, a Geohash-based location privacy protection scheme for location-based services. GLPS enhances user privacy by obscuring exact locations from servers, improving security against various privacy attacks.

Keywords:
Geohash codelocation privacy protectionlocation semanticslocation-based services

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Area of Science:

  • Computer Science
  • Information Security
  • Mobile Computing

Background:

  • Location-based services (LBSs) are integral to mobile applications, generating significant revenue but posing privacy risks.
  • Existing LBS privacy schemes often rely on centralized, trusted anonymous servers, a vulnerable assumption in real-world scenarios.
  • The release of precise location and query data in LBSs heightens the risk of personal privacy breaches.

Purpose of the Study:

  • To propose a novel Geohash-based location privacy protection scheme (GLPS) for snapshot queries.
  • To address the limitations of centralized architectures and the assumption of trustworthy anonymous servers in LBS privacy.
  • To enhance the privacy protection capabilities of LBSs against various sophisticated attacks.

Main Methods:

  • GLPS utilizes Geohash encoding to transform precise user coordinates into privacy-preserving location codes.
  • On the user side, Geohash codes mask exact locations sent to anonymous servers.
  • On the server side, Geohash codes and GL-Trees facilitate k-anonymous query set generation, obscuring user locations.

Main Results:

  • Experimental evaluations demonstrate GLPS offers robust privacy protection and good performance.
  • GLPS effectively mitigates privacy risks associated with centralized architectures and untrusted servers.
  • The scheme successfully resists diverse privacy attacks, including those based on background knowledge and identity association.

Conclusions:

  • GLPS provides a decentralized approach to location privacy in LBSs, removing reliance on server trustworthiness.
  • The Geohash-based method enhances user privacy against various adversarial techniques.
  • GLPS presents a viable solution for securing location data in the expanding landscape of mobile applications.