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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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