Privacy-Preserving Data Sharing and Analytics with Differential Privacy

Dartmouth Events

Privacy-Preserving Data Sharing and Analytics with Differential Privacy

Li Xiong: While Big Data promises significant value, it also raises increasing privacy concerns.

Thursday, January 26, 2017
4:30pm-5:30pm
Kemeny Hall 007
Intended Audience(s): Public
Categories: Lectures & Seminars

While Big Data promises significant value, it also raises increasing privacy concerns.  In this talk, I will describe our efforts towards a comprehensive privacy-preserving data sharing and analytics framework. Following an overview of the framework, we discuss two settings based on state-of-the-art differential privacy techniques: 1) aggregated data sharing for data mining and analytics, and 2) individual location sharing for location based services.  For aggregated sharing, I will present several technical solutions for handing different types of data including sequential and time series data, using medical and spatiotemporal data mining applications.  For individual data sharing, I will present our approach towards a rigorous and customizable privacy notion extending the differential privacy framework for location protection, with location based applications such as nearest POI search and geospatial crowdsourcing.

Li Xiong is  Professor of Computer Science (and Biomedical Informatics) and holds a Winship Distinguished Research Professorship at Emory University. She has 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 and her research group, Assured Information Management and Sharing (AIMS), conduct research that addresses both fundamental and applied questions at the interface of data privacy and security, spatiotemporal data management, and health informatics. Li has published over 100 papers in premier journals and conferences including TKDE, VLDB, ICDE, CCS, and WWW, and has received four best paper awards.  She currently serves as associate editor for IEEE Transactions on Knowledge and Data Engineering (TKDE) and  numerous program committees for data management and data security conferences.  She is a recipient of a Google Research Award, IBM Faculty Innovation Award, Cisco Research Award, and Woodrow Wilson Fellowship.  Her research is supported by NSF (National Science Foundation), NIH (National Institute of Health), AFOSR (Air Force Office of Scientific Research), and PCORI (Patient-Centered Outcomes Research Institute).

For more information, contact:
Sandra Hall

Events are free and open to the public unless otherwise noted.