begood Posted March 17, 2010 Report Posted March 17, 2010 Social-networking sites have grown tremendously in popularity in recent years. Services such as Facebook and MySpace allow millions of users to create online profiles and to share details of their personal lives with vast networks of friends, and often, strangers. Inevitably, the disclosure of personal information has implications on users privacy: digital stalking and identity theft are some of the most common threats. Unfortunately, even sophisticated users who value privacy will often compromise it to improve their presence in the virtual world. They know that loss of control over their personal information poses a long-term threat, but they cannot assess the overall and long-term risk accurately enough to compare it to the short-term gain. Even worse, setting the privacy preferences in online services is often a complicated and time-consuming task that users usually skip. To address these issues, we are developing mechanisms and platforms to measure and monitor users privacy risks and help them easily manage their information sharing. In this talk, we will introduce our work in this area, and also discuss how it work can be incorporated with OpenSocial.Speaker Bio:Kun Liu, Ph.D., is a postdoctoral researcher at IBM Almaden Research Center. He received his Ph.D. from University of Maryland Baltimore County in 2007. His research interests include data mining, social-network analysis and text analytics. His featured work is in the area of privacy-preserving data mining, where he developed advanced privacy and risk management techniques that greatly facilitate the integration, sharing and analysis of data owned by different parties without compromising their privacy. More information about him can be found at Kun Liu at University of Maryland Baltimore County (UMBC)Towards Privacy Aware OpenSocial Applications (IBM Research) Tutorial Quote
