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Issue No.03 - May/June (2011 vol.15)
pp: 13-19
Danesh Irani , Georgia Institute of Technology
Steve Webb , Georgia Institute of Technology
Calton Pu , Georgia Institute of Technology
Kang Li , University of Georgia
ABSTRACT
<p>Most people have multiple accounts on different social networks. Because these networks offer various levels of privacy protection, the weakest privacy policies in the social network ecosystem determine how much personal information is disclosed online. A new information leakage measure quantifies the information available about a given user. Using this measure makes it possible to evaluate the vulnerability of a user's social footprint to two known attacks: physical identification and password recovery. Experiments show the measure's usefulness in quantifying information leakage from publicly crawled information and also suggest ways of better protecting privacy and reducing information leakage in the social Web.</p>
INDEX TERMS
Social networks, personal information leakage, security and privacy
CITATION
Danesh Irani, Steve Webb, Calton Pu, Kang Li, "Modeling Unintended Personal-Information Leakage from Multiple Online Social Networks", IEEE Internet Computing, vol.15, no. 3, pp. 13-19, May/June 2011, doi:10.1109/MIC.2011.25
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