Abstract: Differential Privacy provides a robust concept of privacy through a mathematical framework for quantifying and managing privacy risks. It is studied in the context of the collection, analysis, and release of aggregate statistics ranging from simple statistical estimations to machine learning. It is an emerging topic with growing interest as an approach for satisfying legal requirements for privacy protection of personal information. Differential privacy can be viewed as a technical solution for protecting individual privacy to meet legal or policy requirements for disclosure limitation while analyzing and sharing personal data. Using examples and some mathematical formalism, this talk will introduce differential privacy concepts including the definition of differential privacy, how differentially private analyses are constructed, and how these can be used in practice.
Bio: Veena Mendiratta is an applied researcher in network reliability and analytics at Nokia Bell Labs based in Naperville, Illinois, USA. Her research interests include network dependability, software reliability engineering, programmable networks resiliency, and telecom data analytics. Current work is focused on network reliability and analytics – architecting and modeling the reliability of next-generation programmable networks; and the development of analytics-based algorithms for anomaly detection, network slicing and network control for improving network performance and reliability. She has led projects on customer experience analytics using data mining and social network analysis techniques, and the development of algorithms and visual analytics for anomaly detection in telecommunications networks. She is a member of the SIAM Visiting Lecturer Program, Life Member of SIAM, Senior Member of IEEE, Member of INFORMS; member of ASA; and was a Fulbright Specialist Scholar for 5 years during which time she visited universities in India, Norway and New Zealand. She holds a B.Tech in engineering from IIT-Delhi, India, and a Ph.D. in operations research from Northwestern University, USA.