Abstract
Technologies able to track moving objects such as GPS, GSM, and RFID, have been well-adopted worldwide since the end of the 20th century. As a result, companies and governments manage and control huge spatio-temporal databases, whose publication could lead to previously unknown knowledge such as human behaviour patterns or new road traffic trends (e.g., through Data Mining). Aimed at properly balancing data utility with users’ privacy rights, several microaggregation-based methods for publishing movement data have been proposed. These methods are reviewed in this book chapter. We highlight challenges in the three stages of the microaggregation process namely, clustering, obfuscation, and privacy and utility evaluation. We also address some of these challenges by presenting yet another microaggregation-based method for privacy-preserving publication of spatio-temporal databases.
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Acknowledgments
The second author is partially supported by the Government of Catalonia through an ICREA Acadèmia Prize. The following partial supports are also gratefully acknowledged: the Spanish Government under projects TIN2011-27076-C03-01 “CO-PRIVACY” and CONSOLIDER INGENIO 2010 CSD2007-00004 “ARES”, and the European Commission under FP7 projects “DwB” and “Inter-Trust”. The second author is with the UNESCO Chair in Data Privacy, but the views expressed in this paper neither necessarily reflect the position of UNESCO nor commit that organization.
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Trujillo-Rasua, R., Domingo-Ferrer, J. (2015). Privacy in Spatio-Temporal Databases: A Microaggregation-Based Approach. In: Navarro-Arribas, G., Torra, V. (eds) Advanced Research in Data Privacy. Studies in Computational Intelligence, vol 567. Springer, Cham. https://doi.org/10.1007/978-3-319-09885-2_11
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DOI: https://doi.org/10.1007/978-3-319-09885-2_11
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