Black Hat //Webcast 39
Faces of Facebook: Privacy in the Age of Augmented Reality
// Alessandro Acquisti
We investigate the feasibility of combining publicly available Web 2.0 data with off-the-shelf face recognition software for the purpose of large-scale, automated individual re-identification. Two experiments demonstrated the ability of identifying individuals online (on a dating site where individuals protect their identities by using pseudonyms) and offline (in a public space), based on photos made publicly available on a social network site.
A third proof-of-concept experiment illustrated the ability of inferring individuals' personal or sensitive information (their interests and Social Security numbers) from their faces, by combining face recognition, data mining algorithms, and statistical re-identification techniques. The results highlight the implications of the inevitable convergence of face recognition technology and increasing online self-disclosures, and the emergence of ``personally predictable'' information. They raise questions about the future of privacy in an "augmented" reality world in which online and offline data will seamlessly blend.
Alessandro Acquisti is an Associate Professor of Information Technology and Public Policy at the Heinz College, Carnegie Mellon University. He is the co-director of the CMU Center for Behavioral Decision Research (CBDR), a member of Carnegie Mellon Cylab, and a fellow of the Ponemon Institute. His work investigates the economic and social impact of IT, and in particular the economics and behavioral economics of privacy and information security, as well as privacy in online social networks.