Dr. Li Xiong is an Associate Professor in the Department of Mathematics and Computer Science and the Department of Biomedical Informatics at Emory University where she directs the Assured Information Management and Sharing (AIMS) research group. She holds a PhD from Georgia Institute of Technology, an MS from Johns Hopkins University, and a BS from University of Science and Technology of China, all in Computer Science. She also worked as a software engineer in IT industry for several years prior to pursuing her doctorate. Her areas of research are in data privacy and security, distributed and spatio-temporal data management, and health informatics. She has published about 80 papers in peer reviewed journals and conferences with two best paper awards. She is a recent recipient of the Career Enhancement Fellowship by Woodrow Wilson Foundation. Her research has been supported by the National Science Foundation (NSF), the Air Force Office of Scientific Research (AFOSR), the Patient-Centered Outcomes Research Institute (PCORI), the National Institutute of Health (NIH), and industry awards including Cisco Research Award and IBM Faculty Innovation Award.
TITLE: Making Private User Data Accessible for Information Retrieval Research:
Data Sharing with Differential Privacy
Almost a decade has passed since the infamous AOL data leak.
Up till today, data privacy concerns continue to prohibit valuable user data such as query logs and
web browsing sessions to be shared and used for Information Retrieval (IR) research.
As a result, lack of large scale datasets is still one of the major barriers facing academic IR researchers. This talk will give an overview of the recent developments in building and sharing statistical and synthetic datasets based on private data with the rigorous differential privacy guarantee. Then we will focus on techniques we have developed for sharing sequential data under differential privacy, addressing challenges such as high dimensionality and high correlations, which are also common characteristics in user behavior data. Empirical studies using real-world web browsing data will demonstrate the feasibility as well as challenges of applying differential privacy on user behavior data for IR research.
Dr. Simson L. Garfinkel is a computer scientist at the National Institute of Standards and Technology. Garfinkel's research interests include digital forensics, usable security, data fusion, information policy and terrorism. He holds seven US patents for his computer-related research and has published dozens of research articles on security and digital forensics. He is an ACM Fellow and an IEEE Senior Member, as well as a member of the National Association of Science Writers.
Garfinkel is the author or co-author of fourteen books on computing. He is perhaps best known for his book Database Nation: The Death of Privacy in the 21st Century. Garfinkel's most successful book, Practical UNIX and Internet Security (co-authored with Gene Spafford), has sold more than 250,000 copies and been translated into more than a dozen languages since the first edition was published in 1991.
Garfinkel is also a journalist and has written more than a thousand articles about science, technology, and technology policy in the popular press since 1983. He has won numerous national journalism awards, including the Jesse H. Neal National Business Journalism Award two years in a row for his "Machine shop" series in CSO magazine. Today he mostly writes for Technology Review Magazine and the technologyreview.com website.
As an entrepreneur, Garfinkel founded five companies between 1989 and 2000. Two of the most successful were Vineyard.NET, which provided Internet service on Martha's Vineyard to more than a thousand customers from 1995 through 2005, and Sandstorm Enterprises, an early developer of commercial computer forensic tools.
Garfinkel received three Bachelor of Science degrees from MIT in 1987, a Master's of Science in Journalism from Columbia University in 1988, and a Ph.D. in Computer Science from MIT in 2005.