Abstract
In this work, we study the problem of anonymity-preserving data publishing in moving objects databases. In particular, the trajectory of a mobile user on the plane is no longer a polyline in a two-dimensional space, instead it is a two-dimensional surface: we know that the trajectory of the mobile user is within this surface, but we do not know exactly where. We transform the surface’s boundary poly-lines to dual points and we focus on the information distortion introduced by this space translation. We develop a set of efficient spatio-temporal access methods and we experimentally measure the impact of information distortion by comparing the performance results of the same spatio-temporal range queries executed on the original database and on the anonymized one.
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Sioutas, S., Magkos, E., Karydis, I., Verykios, V.S. (2010). Uncertainty for Anonymity and 2-Dimensional Range Query Distortion. In: Domingo-Ferrer, J., Magkos, E. (eds) Privacy in Statistical Databases. PSD 2010. Lecture Notes in Computer Science, vol 6344. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15838-4_8
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DOI: https://doi.org/10.1007/978-3-642-15838-4_8
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