Dario Freni

Privacy in geo-social networks: proximity notification with untrusted service providers and curious buddies

A major feature of the emerging geo-social networks is the ability to notify a user when any of his friends (also called buddies) happens to be geographically in proximity. This proximity service is usually offered by the network itself or by a third party service provider (SP) using location data acquired from the users. This paper provides a rigorous theoretical and experimental analysis of the existing solutions for the location privacy problem in proximity services. This is a serious problem for users who do not trust the SP to handle their location data and would only like to release their location information in a generalized form to participating buddies. The paper presents two new protocols providing complete privacy with respect to the SP and controllable privacy with respect to the buddies. The analytical and experimental analysis of the protocols takes into account privacy, service precision, and computation and communication costs, showing the superiority of the new protocols compared to those appeared in the literature to date. The proposed protocols have also been tested in a full system implementation of the proximity service.

Preserving location and absence privacy in geo-social networks

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 publisher being aware of the privacy preferences of those users. Moreover, this content is often accessible to multiple users. This renders it difficult for GeoSN users to control which information about them is available and to whom it is available. This paper addresses two privacy threats that occur in GeoSNs: location privacy and absence privacy. The former concerns the availability of information about the presence of users in specific locations at given times, while the latter concerns the availability of information about the absence of an individual from specific locations during given periods of time. The challenge addressed is that of supporting privacy while still enabling useful services. We believe this is the first paper to formalize these two notions of privacy and to propose techniques for enforcing them. The techniques offer privacy guarantees, and the paper reports on empirical performance studies of the techniques.

Spatial generalisation algorithms for LBS privacy preservation

Spatial generalisation has been recently proposed as a technique for the anonymisation of requests in location based services. This article provides a formal characterisation of a privacy attack that has been informally described in previous work, and presents a new generalisation algorithm that is proved to be a safe defense against that attack. The article also reports the results of an extensive experimental study, comparing the new algorithm with the ones that have been previously proposed in the literature.

Pcube: A System to Evaluate and Test Privacy-Preserving Proximity Services

Proximity services are a particular class of location-based services (LBS) in which a subscriber is alerted when other participants (called buddies) are nearby. Existing works in the field of privacy preservation in LBS propose techniques specifically designed for this type of service. The objective of this demo is to present the Pcube system that makes it possible to visually show the different performances of these techniques in terms of privacy protection and precision of the service. The system includes a server component providing the proximity service, a web-based client application and a client application for mobile devices. Four different privacy-preserving techniques existing in literature have been implemented and will be compared during the demo, with a particular focus on the evaluation of the recently proposed Longitude protocol.

Hide & Crypt: Protecting Privacy in Proximity-Based Services

A particular class of location based services, called friend finder , is becoming very popular. Using this kind of service, a subscriber obtains to know location information about other participants (called buddies). Current commercial applications of this service imply the acquisition by the service provider of the user location at the best possible precision. This can discourage many users to use this service, since the precise location is a private information. We present a privacy-aware friend finder system called Hide&Crypt that notifies a user whether her buddies are within a user-specified threshold distance. The user can specify her location privacy requirements both with respect to the service provider and to the other buddies. The system includes a server application, and clients for mobile devices and desktop computers.