PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Andrienko G., Andrienko N., Giannotti F., Monreale A., Pedreschi D., Rinzivillo S. A generalisation-based approach to anonymising movement data. In: The 13th AGILE conference on Geographic Information Science (Guimar„es, Portugal, 10-14 May 2010). Proceedings, AGILE Conference - Online proceedings, 2010.
 
 
Abstract
(English)
The possibility to collect, store, disseminate, and analyze data about movements of people raises very serious privacy concerns, given the sensitivity of the information about personal positions. In particular, sensitive information about individuals can be uncovered with the use of data mining and visual analytics methods. In this paper we present a method for the generalization of trajectory data that can be adopted as the first step of a process to obtain k-anonymity in spatio-temporal datasets. We ran a preliminary set of experiments on a real-world trajectory dataset, demonstrating that this method of generalization of trajectories preserves the clustering analysis results.
URL: http://plone.itc.nl/agile_old/Conference/2010-guimaraes/ShortPapers_PDF/122_DOC.pdf
Subject Privacy
Clustering
Spatio-temporal Clustering
H.2.8 Database Applications
K.4.1 Public Policy Issues


Icona documento 1) Download Document PDF


Icona documento Open access Icona documento Restricted Icona documento Private

 


Per ulteriori informazioni, contattare: Librarian http://puma.isti.cnr.it

Valid HTML 4.0 Transitional