Geosocial networks and applications, such as Foursquare, Gowalla and Facebook places, are designed to encourage their users to share their geolocated data. Among all the Personal Identifiable Information (PII), learning the location of an individual is one of the greatest threat against his privacy. For instance, the spatio-temporal data of an individual can be used to infer the location of his home and workplace, to trace his movements and habits, to learn information about his center of interests or even to detect a change from his usual behaviour. In this paper, we provide a comparative privacy analysis of several existing geosocial networks. We first describe the main characteristics of geosocial networks and then we briefly review the systems on which we have focus in this study. Afterwards, we describe the privacy and security criteria that we have identified before evaluating and comparing the different geosocial networks in the light of these criteria. Finally, we finish with a discussion and some recommendations on how to enhance the protection of privacy in geosocial networks.
[1]
Sébastien Gambs,et al.
Show me how you move and I will tell you who you are
,
2010,
SPRINGL '10.
[2]
Lise Getoor,et al.
To join or not to join: the illusion of privacy in social networks with mixed public and private user profiles
,
2009,
WWW '09.
[3]
Gaetano Borriello,et al.
Extracting places from traces of locations
,
2004,
MOCO.
[4]
Esma Aïmeur,et al.
Towards a Privacy-Enhanced Social Networking Site
,
2010,
2010 International Conference on Availability, Reliability and Security.
[5]
Pierangela Samarati,et al.
Location privacy in pervasive computing
,
2008
.
[6]
Philippe Golle,et al.
On the Anonymity of Home/Work Location Pairs
,
2009,
Pervasive.
[7]
Danah Boyd,et al.
Social Network Sites: Definition, History, and Scholarship
,
2007,
J. Comput. Mediat. Commun..