Proceedings of the 19th ACM International Conference on Information and Knowledge Management 2010
DOI: 10.1145/1871437.1871480
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Preserving location and absence privacy in geo-social networks

Abstract: Online social networks often involve very large numbers of users who share very large volumes of content. This content is increasingly being tagged with geo-spatial and temporal coordinates that may then be used in services. For example, a service may retrieve photos taken in a certain region. The resulting geo-aware social networks (GeoSNs) pose privacy threats beyond those found in location-based services. Content published in a GeoSN is often associated with references to multiple users, without the publish… Show more

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Cited by 67 publications
(42 citation statements)
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“…In a recent article [4], we propose two solutions based on spatial and temporal cloaking to preserve location privacy in the context of a content-centric GeoSN that supports user tagging. This setting calls for careful adaptation of techniques known from traditional location-based services.…”
Section: Protecting Location Privacymentioning
confidence: 99%
See 1 more Smart Citation
“…In a recent article [4], we propose two solutions based on spatial and temporal cloaking to preserve location privacy in the context of a content-centric GeoSN that supports user tagging. This setting calls for careful adaptation of techniques known from traditional location-based services.…”
Section: Protecting Location Privacymentioning
confidence: 99%
“…The notion of absence privacy is relatively new, and only one proposal for absence privacy protection exists, presented for content-centric GeoSNs [4]. The privacy preferences expressed by the users are called absence privacy regions (APRs).…”
Section: Protecting Absence Privacymentioning
confidence: 99%
“…Freni et al [27] treat location privacy in social networks. Of particular interest is the definition of absence privacy to protect the fact that a user is absent at certain location points (reducing burglary risks).…”
Section: Related Workmentioning
confidence: 99%
“…The privacy preserving technology of location based on the location service and the privacy preserving technology of the trajectory data have achieved some research results, but they cannot be directly applied to mobile social networks. In recent years researchers have made studies on the privacy in mobile social networks, such as the location inference attack [9] in mobile social networks, the location privacy preserving and the absence privacy preserving [10] in mobile social networks, the location privacy preserving of proximity based services [11,12], and so on. Making use of the prefix trees, the authors in [13] have achieved privacy protection of trajectory k-anonymity.…”
Section: Introductionmentioning
confidence: 99%