Privacy-Preserving Distributed Movement Data Aggregation

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TitlePrivacy-Preserving Distributed Movement Data Aggregation
Publication TypeBook Chapter
Year of Publication2013
AuthorsMonreale, A, Wang, H, Pratesi, F, Rinzivillo, S, Pedreschi, D, Andrienko, G, Andrienko, N
Secondary AuthorsVandenbroucke, D, Bucher, B, Crompvoets, J
Book TitleGeographic Information Science at the Heart of Europe
Series TitleLecture Notes in Geoinformation and Cartography
Pagination225-245
PublisherSpringer International Publishing
ISBN Number978-3-319-00614-7
AbstractWe propose a novel approach to privacy-preserving analytical processing within a distributed setting, and tackle the problem of obtaining aggregated information about vehicle traffic in a city from movement data collected by individual vehicles and shipped to a central server. Movement data are sensitive because people’s whereabouts have the potential to reveal intimate personal traits, such as religious or sexual preferences, and may allow re-identification of individuals in a database. We provide a privacy-preserving framework for movement data aggregation based on trajectory generalization in a distributed environment. The proposed solution, based on the differential privacy model and on sketching techniques for efficient data compression, provides a formal data protection safeguard. Using real-life data, we demonstrate the effectiveness of our approach also in terms of data utility preserved by the data transformation.
URLhttp://dx.doi.org/10.1007/978-3-319-00615-4_13
DOI10.1007/978-3-319-00615-4_13
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