53
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2009-04-06 19:09:58
2009-04-07 14:02:26
2009-04-06 19:09:58
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Squicciarini
Anna C.
The Pennsylvania State University
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Shehab
Mohamed
University of North Carolina at Charlotte
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Paci
Federica
Purdue University
Collective Privacy Management in Social Networks
pub
public
paper
Social Networking is one of the major technological phe-
nomena of the Web 2.0, with hundreds of millions of people
participating. Social networks enable a form of self expres-
sion 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 mech-
anism 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 solu-
tion 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 pro-
mote 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 pro-
posed. In the paper, we also show a proof-of-concept appli-
cation, 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.
2009-04
521-521
18th International World Wide Web Conference
Madrid, Spain
April 20th-24th, 2009
conference
TRUE
53
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53
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application/pdf
en
public
p521.pdf
published
p521.pdf
904585
http://www2009.eprints.org/53/1/p521.pdf