Collaborative and privacy-aware sensing for observing urban movement patterns

dc.contributor.author Goncalves,N en
dc.contributor.author Jose,R en
dc.contributor.author Carlos Baquero en
dc.date.accessioned 2018-02-14T16:19:04Z
dc.date.available 2018-02-14T16:19:04Z
dc.date.issued 2014 en
dc.description.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. © 2014 Springer-Verlag Berlin Heidelberg. en
dc.identifier.uri http://repositorio.inesctec.pt/handle/123456789/7487
dc.identifier.uri http://dx.doi.org/10.1007/978-3-642-54568-9-4 en
dc.language eng en
dc.relation 5596 en
dc.rights info:eu-repo/semantics/openAccess en
dc.title Collaborative and privacy-aware sensing for observing urban movement patterns en
dc.type conferenceObject en
dc.type Publication en
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