Privacy and security for online social networks: challenges and opportunities
IEEE Network: The Magazine of Global Internetworking
Toward a behavioral approach to privacy for online social networks
SocInfo'10 Proceedings of the Second international conference on Social informatics
Measuring profile distance in online social networks
Proceedings of the International Conference on Web Intelligence, Mining and Semantics
Analyzing facebook privacy settings: user expectations vs. reality
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
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Recent research identifies a growing privacy problemthat exists within Online Social Networks (OSNs). Severalstudies have shown how easily strangers can extract personaldata about users from the network. Other studies haveshown that an extremely small percentage of OSN userschange their permissive default privacy settings. Complementary systems have been proposed to provide privacy for OSN users but many of them seem to be costly in terms ofsimplicity or management overhead. Furthermore, severalof these approaches seem to violate the social aspect of online social networks by reducing the problem to manual access management with cryptography. Under this setting, instead of freely sharing one’s data with its friends, a user will share data only with those friends possessing allowed cryptographic keys. While these systems will indeed provide additional privacy for user data, they will not address a more fundamental problem that exists within OSNs: the inability of the network to easily and automatically distinguish relationship quality between a user and its friends. This distinction may be critical in providing a simple, automatic privacy mechanism for OSNs. We propose a unique approach utilizing interactions between friends as the currency for data access. This model operates within the bounds of social networks while incurring minimum additional management overhead for the user. As a first step, we consider interaction intensity as a proxy for relationship quality for the purpose of making privacy decisions. Although we present our ideas from the privacy perspective we also discuss how our approach can be used to support the development of more secure social network based applications.