Social network data has been increasingly made publicly available and analyzed in a wide spectrum of application domains. The practice of publishing social network data has brought privacy concerns to the front. Serious concerns on privacy protection in social networks have been raised in recent years. Realization of the promise of social networks data requires addressing these concerns. This paper considers the privacy disclosure in social network data publishing. In this paper, we present a systematic analysis of the various risks to privacy in publishing of social network data. We identify various attacks that can be used to reveal private information from social network data. This information is useful for developing practical countermeasures against the privacy attacks.
History
Pagination
165-174
Location
Melbourne, Victoria
Start date
2011-10-24
End date
2011-10-26
ISSN
0302-9743
ISBN-13
9783642246494
Language
eng
Publication classification
E1 Full written paper - refereed
Copyright notice
2011, Springer-Verlag Berlin
Extent
38
Editor/Contributor(s)
Xiang Y, Cuzzocrea A, Hobbs M, Zhou W
Title of proceedings
ICA3PP 2011 : Proceedings of the 11th Algorithms and Architectures for Parallel Processing International Conference
Event
Algorithms and Architectures for Parallel Processing. Conference (11th : 2011 : Melbourne, Victoria)