TY - GEN
T1 - Collective privacy management in Social networks
AU - Squicciarini, Anna C.
AU - Shehab, Mohamed
AU - Paci, Federica
PY - 2009
Y1 - 2009
N2 - Social Networking is one of the major technological phenomena of the Web 2.0, with hundreds of millions of people participating. Social networks enable a form of self expression for users, and help them to socialize and share content with other users. In spite of the fact that content sharing represents one of the prominent features of existing Social Network sites, Social Networks yet do not support any mechanism for collaborative management of privacy settings for shared content. In this paper, we model the problem of collaborative enforcement of privacy policies on shared data by using game theory. In particular, we propose a solution that offers automated ways to share images based on an extended notion of content ownership. Building upon the Clarke-Tax mechanism, we describe a simple mechanism that promotes truthfulness, and that rewards users who promote co-ownership. We integrate our design with inference techniques that free the users from the burden of manually selecting privacy preferences for each picture. To the best of our knowledge this is the first time such a protection mechanism for Social Networking has been proposed. In the paper, we also show a proof-of-concept application, which we implemented in the context of Facebook, one of today's most popular social networks. We show that supporting these type of solutions is not also feasible, but can be implemented through a minimal increase in overhead to end-users. Copyright is held by the International World Wide Web Conference Committee (IW3C2).
AB - Social Networking is one of the major technological phenomena of the Web 2.0, with hundreds of millions of people participating. Social networks enable a form of self expression for users, and help them to socialize and share content with other users. In spite of the fact that content sharing represents one of the prominent features of existing Social Network sites, Social Networks yet do not support any mechanism for collaborative management of privacy settings for shared content. In this paper, we model the problem of collaborative enforcement of privacy policies on shared data by using game theory. In particular, we propose a solution that offers automated ways to share images based on an extended notion of content ownership. Building upon the Clarke-Tax mechanism, we describe a simple mechanism that promotes truthfulness, and that rewards users who promote co-ownership. We integrate our design with inference techniques that free the users from the burden of manually selecting privacy preferences for each picture. To the best of our knowledge this is the first time such a protection mechanism for Social Networking has been proposed. In the paper, we also show a proof-of-concept application, which we implemented in the context of Facebook, one of today's most popular social networks. We show that supporting these type of solutions is not also feasible, but can be implemented through a minimal increase in overhead to end-users. Copyright is held by the International World Wide Web Conference Committee (IW3C2).
UR - http://www.scopus.com/inward/record.url?scp=77954588562&partnerID=8YFLogxK
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U2 - 10.1145/1526709.1526780
DO - 10.1145/1526709.1526780
M3 - Conference contribution
AN - SCOPUS:77954588562
SN - 9781605584874
T3 - WWW'09 - Proceedings of the 18th International World Wide Web Conference
SP - 521
EP - 530
BT - WWW'09 - Proceedings of the 18th International World Wide Web Conference
T2 - 18th International World Wide Web Conference, WWW 2009
Y2 - 20 April 2009 through 24 April 2009
ER -