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- W2024625296 abstract "Geo-social networking systems, such as Foursquare and Face-book Places, where users perform interactions based on their self-reported locations are growing fast nowadays. The location-rich social network data collected in such systems could be of research interest for various purposes. However, such datasets are at the risk of user re-identification and consequently privacy violation of the involved users if they are not adequately anonymzied. In this paper, we study the problem of anonymizing a geo-social network dataset, based on adversarial knowledge on location information of its users. We introduce k-anonymity-based properties for guaranteeing anonymity based on location information, provide a realistic model of location data in geo-social networks, and propose corresponding anonymization algorithms. We also evaluate the proposed solutions using a synthetic GSN dataset." @default.
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- W2024625296 date "2011-11-01" @default.
- W2024625296 modified "2023-10-05" @default.
- W2024625296 title "Anonymizing geo-social network datasets" @default.
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- W2024625296 doi "https://doi.org/10.1145/2071880.2071886" @default.
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