Google Tech Talk May 19, 2009 ABSTRACT Presented by Kun Liu. [note - apologies for the overscanned slides. You can view the slides here: http://www.slideshare.net/starrysky2/towards-privacyaware-opensocial-applications ] 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 Info: 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 http://www.cs.umbc.edu/~kunliu1 Evimaria Terzi, Ph.D., has been a researcher at IBM Almaden since June 2007. She obtained her Ph.D. from the University of Helsinki, Finland, in January 2007; her M.Sc. from Purdue University in 2002; and her B.Sc. from the University of Thessaloniki, Greece, in 2000. Her research interests are in the area of algorithmic data mining with applications to social-network analysis, information retrieval, and databases. More information about her can be found at http://www.cs.helsinki.fi/u/terzi/ Dr. E. Michael Maximilien, (aka max) is a research staff member at IBM's Almaden Research Center in San Jose, California. Prior to joining ARC, Max spent ten years at IBM's Research Triangle Park, N.C., in software development and architecture. Max led various small- to medium-sized teams, designing and developing enterprise and embedded Java? software; he is a founding member and contributor to three worldwide Java and UML industry standards. Max's primary research interests lie in distributed systems and software engineering for the Web, especially Web APIs and services, mashups, Web 2.0, cloud computing, SOA (service-oriented architecture), social software, and Agile methods and practices. Max is also active participants and contributor to communities related to Ruby, Ruby on Rails, and Agile methods and practices, inside and outside of IBM. Reach Max via his Web site (www.maximilien.com) and blog (blog.maximilien.com).
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