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Towards trajectory anonymisation using multi-dimensional index structures

Author

Listed:
  • Ahmed Almasrahi
  • Heechang Shin
  • Haibing Lu

Abstract

Trajectory datasets are increasingly available due to the technological advances in location-sensing devices, wireless technologies, and hand-held devices. However, the datasets also causes consumer privacy concerns. This paper addresses the privacy issues by using the internal structure of R-tree, a multi-dimensional index structure. The benefit of using R-tree is that it clusters trajectories in a way that their bounding spatiotemporal extension is minimised, thus achieving better quality in the anonymised database. This is a desirable property of the resulting anonymised database. In order to improve the quality of service requirements, a novel algorithm has been proposed.

Suggested Citation

  • Ahmed Almasrahi & Heechang Shin & Haibing Lu, 2016. "Towards trajectory anonymisation using multi-dimensional index structures," International Journal of Business Continuity and Risk Management, Inderscience Enterprises Ltd, vol. 6(4), pages 304-313.
    • Handle: RePEc:ids:ijbcrm:v:6:y:2016:i:4:p:304-313
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