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- W1722893734 abstract "The information infrastructure that pervades urban environments represents a major opportunity for collecting information about Human mobility. However, this huge potential has been undermined by the overwhelming privacy risks that are associated with such forms of large scale sensing. In this research, we are concerned with the problem of how to enable a set of autonomous sensing nodes, e.g. a Bluetooth scanner or a Wi-Fi hotspot, to collaborate in the observation of movement patterns of individuals without compromising their privacy. We describe a novel technique that generates Precedence Filters and allows probabilistic estimations of sequences of visits to monitored locations and we demonstrate how this technique can combine plausible deniability by an individual with valuable information about aggregate movement patterns." @default.
- W1722893734 created "2016-06-24" @default.
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- W1722893734 date "2014-01-01" @default.
- W1722893734 modified "2023-10-17" @default.
- W1722893734 title "Collaborative and Privacy-Aware Sensing for Observing Urban Movement Patterns" @default.
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- W1722893734 doi "https://doi.org/10.1007/978-3-642-54568-9_4" @default.
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