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Dr Bo Luo is currently an assistant professor with EECS department at the University of Kansas. He received Ph.D. degree from The Pennsylvania State University in 2008, an M. Phil degree from the Chinese University of Hong Kong in 2003, and a B.E. from University of Sciences and Technology of China in 2001. He is interested in information retrieval, information security and privacy. He has published in top conferences and journals such as ACM CCS, ACM Multimedia, CIKM, INFOCOM, IEEE TKDE, IEEE TIFS etc.

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In recent years, online social networks like Facebook, Twitter and Google+ have attracted large numbers of users, who willingly share their private information with others. With the advancement of web technology, on the other hand, it becomes easier for malicious applications to pose real privacy threats on such SNS users. Unfortunately, existing privacy protection approaches fall short as they either prevent users from socialization, or mostly focus on social connections instead of contents. We argue that contents such as user attributes and unstructured text messages are critical in privacy protection. In particular, we will discuss: (1) the risks associated with attributes and contents, in particular, attribute-reidentification attacks; (2) identification of social circles and exploiting social circles for privacy protection; (3) predicting social network user behaviors, and identifying high-risk nodes in social circles.

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