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Volume 2 Issue 1


Towards Trajectory Anonymization: a Generalization-Based Approach

Mehmet Ercan Nergiz(a), Maurizio Atzori(b), Yücel Saygın(a),(*), Barıʂ Güç(c)

Transactions on Data Privacy 2:1 (2009) 47 - 75

Abstract, PDF

(a) Sabanci University; Istanbul; Turkey. e-mail: {ercann, ysaygin}@sabanciuniv.edu

(b) KDD Lab; ISTI-CNR; Pisa; Italy. e-mail: atzori@di.unipi.it

(c) Swiss Federal Institute of Technology; Zurich; Switzerland. e-mail: baris@student.ethz.ch


Abstract

Trajectory datasets are becoming popular due to the massive usage of GPS and location-based services. In this paper, we address privacy issues regarding the identification of individuals in static trajectory datasets. We first adopt the notion of k-anonymity to trajectories and propose a novel generalization-based approach for anonymization of trajectories.

* Corresponding author.

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ISSN: 1888-5063; ISSN (Digital): 2013-1631; D.L.:B-11873-2008; Web Site: http://www.tdp.cat/
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Vicenç Torra, Last modified: 00 : 25 December 12 2014.