Fine-Grained Cloaking of Sensitive Positions in Location-Sharing Applications

Damiani, Maria Luisa; Silvestri, Claudio; Bertino, Elisa

doi:10.1109/mprv.2011.18

Cited by 47 publications

(34 citation statements)

References 9 publications

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“…A first step towards an effective protection of sensitive stops is offered by the semantic location cloaking paradigm [Damiani et al 2011]. This paradigm is grounded on the idea that positions may exhibit a different degree of sensitivity depending on the context, in particular the POI (or place) in which the moving person is located.…”

Section: The Protection Of Sensitive Stops In Streaming Applicationsmentioning

confidence: 99%

Semantic trajectories modeling and analysis

et al. 2013

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___________________________________________________________________Focus on movement data has increased as a consequence of the larger availability of such data due to current GPS, GSM, RFID, and sensors techniques. In parallel, interest in movement has shifted from raw movement data analysis to more application-oriented ways of analyzing segments of movement suitable for the specific purposes of the application. This trend has promoted semantically rich trajectories, rather than raw movement, as the core object of interest in mobility studies. This survey provides the definitions of the basic concepts about mobility data, an analysis of the issues in mobility data management, and a survey of the approaches and techniques for i) constructing trajectories from movement tracks, ii) enriching trajectories with semantic information to enable the desired interpretations of movements, and iii) using data mining to analyze semantic trajectories and extract knowledge about their characteristics, in particular the behavioral patterns of the moving objects. Last but not least, the paper surveys the new privacy issues that rise due to the semantic aspects of trajectories.

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Section: The Protection Of Sensitive Stops In Streaming Applicationsmentioning

confidence: 99%

Semantic trajectories modeling and analysis

et al. 2013

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“…Instead, semantic-based approaches are needed, as mentioned in Damiani, Silvestri, and Bertino (2011) and Parent et al (2013). Semantic location cloaking (Damiani et al, 2010(Damiani et al, , 2011) is based on the idea that locations can be more or less sensitive depending on the context, mainly the place where the person is located, and therefore the location granularity disclosed can be adjusted accordingly.…”

Section: Semantic-based Privacy Protectionmentioning

confidence: 99%

Semantic management of moving objects: A vision towards smart mobility

Ilarri

Stojanović

Ray

2015

Expert Systems with Applications

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is an open access repository that collects the work of Arts et Métiers ParisTech researchers and makes it freely available over the web where possible. b s t r a c tThis position paper presents our vision for the semantic management of moving objects. We argue that exploiting semantic techniques in mobility data management can bring valuable benefits to many domains characterized by the mobility of users and moving objects in general, such as traffic management, urban dynamics analysis, ambient assisted living, emergency management, m-health, etc. We present the state-of-the-art in the domain of management of semantic locations and trajectories, and outline research challenges that need to be investigated to enable a full-fledged and intelligent semantic management of moving objects and location-based services that support smarter mobility. We propose a distributed framework for the semantic enrichment and management of mobility data and analyze the potential deployment and exploitation of such a framework.

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“…Simple transformations return a fake position or a coarse regions at predefined granularity. Non trivial obfuscation techniques might include, for example, semantic location cloaking [2]. Below some examples of privacy rules:…”

Section: Privacy Policy Handlermentioning

confidence: 99%

“…• Everywhere, [08:00, 19:00] → SemanticCloaking() specifies that any position in the time interval is mapped onto the map generated by semantic location cloaking [2]. This map contains pre-computed cloaked regions enclosing sensitive places, e.g.…”

Section: Privacy Policy Handlermentioning

confidence: 99%

“…As LPs are potentially untrustworthy, privacy is seriously at stake. Unfortunately, existing privacy-preserving techniques, such as [2] do not protect the position from the LP but exclusively from the LBS provider; moreover, LPs do not generally accept anonymous communications (e.g., onion routing). To more clearly motivate this privacy issue, consider the following scenario in which Alice is subscriber of a LBS.…”

Section: Introductionmentioning

confidence: 99%

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Handling user-defined private contexts for location privacy in LBS

Damiani

Galbiati

2012

Proceedings of the 20th International Conference on Advances in Geographic Information Systems

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We present a privacy-preserving framework for the protection of location from potentially untrustworthy location providers (LP), offering geolocation services to LBS subscribers, across indoor and outdoor settings. This framework, called Placeprint, is built on the metaphor of private place [1]. A private place is a user-defined spatial context which belongs to the personal sphere of an individual, e.g. home. In Placeprint, users equipped with commodity devices, can be geolocated in private places without revealing to the LP their presence. Moreover users can specify context-based privacy rules to forestall the disclosure of private places also to LBS providers. The ultimate goal is to provide users with the capability of exercising flexible control over the disclosure of the position to both LP and LBS provider.

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Fine-Grained Cloaking of Sensitive Positions in Location-Sharing Applications

Cited by 47 publications

References 9 publications

Semantic trajectories modeling and analysis

Semantic trajectories modeling and analysis

Semantic management of moving objects: A vision towards smart mobility

Handling user-defined private contexts for location privacy in LBS

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