Faces of Facebook: Privacy in the Age of Augmented Reality
Mon., Apr 16, 2012
2:00 - 3:00 PM
521 Cory (Hogan room)
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.

Biography: Alessandro Acquisti (http://www.heinz.cmu.edu/~acquisti/) is an Associate Professor of Information Systems and Public Policy at the Heinz College, Carnegie Mellon University (CMU), and a member of Carnegie Mellon CyLab. He is the co-director of CMU Center for Behavioral Decision Research (CBDR), and a member of the National Academies' Committee on Public Response to Alerts and Warnings Using Social Media and Associated Privacy Considerations. He has held visiting positions at the Universities of Rome, Paris, Freiburg, and Harvard; and at Microsoft Research (visiting researcher) and Google (visiting scientist).

Alessandro's research investigates the economics of privacy. His studies have spearheaded the application of behavioral economics to the study of privacy and information security decision making, and the analysis of privacy risks and disclosure behavior in online social networks. His manuscripts have been published in journals across several disciplines (including the Proceedings of the National Academy of Science, the Journal of Consumer Research, the Journal of Marketing Research, Marketing Science, Information Systems Research, the Journal of Comparative Economics, and ACM Transactions), as well as edited books, conference proceedings, and several international conference keynotes. Alessandro has been the recipient of the PET Award for Outstanding Research in Privacy Enhancing Technologies, the IBM Best Academic Privacy Faculty Award, multiple Best Paper awards, and the Heinz College School of Information's Teaching Excellence Award. His research has been supported by awards and grants from the National Science Foundation, the Transcoop Foundation, Microsoft, and Google.

Alessandro has testified in Congress on issues related to privacy policy and consumer behavior, and participated in policy-finding activities of the Federal Trade Commission, DARPA, the European Network and Information Security Agency, and various national privacy commissioner authorities. In 2009, he was the invited co-chair of the cyber-economics track at the National Cyber Leap Year Summit, as part of the NITRD Program, under guidance from the White House's Office of Science and Technology Policy.

Several of Alessandro's findings have been featured in national and international media outlets, including the Economist, the New York Times and New York Times Magazine, the Wall Street Journal, the Washington Post, the Financial Times, Wired.com, NPR, and CNN.

Alessandro holds a PhD from UC Berkeley, and Master degrees from UC Berkeley, the London School of Economics, and Trinity College Dublin. While at Berkeley, he interned a Xerox PARC and Riacs, NASA Ames.
UC Berkeley Networking
Ashwin Pananjady and Orhan Ocal
Last Modification Date: Wednesday, February 10, 2016