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Modeling Unintended Personal-Information Leakage from Multiple Online Social Networks

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4 Author(s)
Irani, D. ; Georgia Inst. of Technol., Atlanta, GA, USA ; Webb, S. ; Pu, C. ; Kang Li

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.

Published in:

Internet Computing, IEEE  (Volume:15 ,  Issue: 3 )