Towards trajectory anonymisation using multi-dimensional index structures. (2016)

• Record Type: Journal Article
• Authors: Almasrahi, Ahmed; Shin, Heechang; Lu, Haibing
• Is Part Of: International journal of business continuity and risk management. Volume 6:Number 4(2016)
• Page Start: 304
• Page End: 313
• Publication Date: 2016
• Subjects: LBS -- loction-based services -- k-anonymity -- security -- privacy protection -- privacy preservation -- trajectory anonymisation -- R-tree -- multidimensional index structures -- clustering -- quality of service -- QoS; Crisis management -- Periodicals; Strategic planning -- Periodicals; Risk management -- Periodicals; 658.405605
• Languages: English
• ISSNs: 1758-2164

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.