Int. J. of Business Continuity and Risk Management   »   2016 Vol.6, No.4

 

 

Title: Towards trajectory anonymisation using multi-dimensional index structures

 

Authors: Ahmed Almasrahi; Heechang Shin; Haibing Lu

 

Addresses:
Department of Information Systems, Hagan School of Business, Iona College, 715 North Avenue, New Rochelle, NY 10801, USA
Department of Information Systems, Hagan School of Business, Iona College, 715 North Avenue, New Rochelle, NY 10801, USA
Department of Operations Management and Information Systems, The Leavey School of Business, Santa Clara University, 500 El Camino Real, Santa Clara, California 95053, USA

 

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.

 

Keywords: LBS; loction-based services; k-anonymity; security; privacy protection; privacy preservation; trajectory anonymisation; R-tree; multidimensional index structures; clustering; quality of service; QoS.

 

DOI: 10.1504/IJBCRM.2016.10002278

 

Int. J. of Business Continuity and Risk Management, 2016 Vol.6, No.4, pp.304 - 313

 

Submission date: 20 Aug 2015
Date of acceptance: 27 Feb 2016
Available online: 28 Dec 2016

 

 

Editors Full text accessAccess for SubscribersPurchase this articleComment on this article