Privacy in the Land of Plenty

Privacy-preserving data analysis has a large literature that spans several disciplines.  “Differential privacy” — a notion tailored to situations in which data are plentiful — has provided a theoretically sound and powerful framework, and given rise to an explosion of research.  We will review the definition of differential privacy, describe some algorithmic contributions, and conclude with a surprising application.

Description:

A presentation by Dr. Cynthia Dwork, Microsoft Research

Time: 4:00 p.m. – 5:15 p.m.

Where: Donald Bren Hall, Room 6011 (directions)

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Privacy-preserving data analysis has a large literature that spans several disciplines.  “Differential privacy” — a notion tailored to situations in which data are plentiful — has provided a theoretically sound and powerful framework, and given rise to an explosion of research.  We will review the definition of differential privacy, describe some algorithmic contributions, and conclude with a surprising application.

Bio

Dr. Cynthia Dwork, Distinguished Scientist at Microsoft Research, is renowned for placing privacy-preserving data analysis on a mathematically rigorous foundation. A cornerstone of this work is differential privacy, a strong privacy guarantee frequently permitting highly accurate data analysis. Dr. Dwork has also made seminal contributions in cryptography and distributed computing, and is a recipient of the Edsger W. Dijkstra Prize, recognizing some of her earliest work establishing the pillars on which every fault-tolerant system has been built for decades. She is a member of the National Academy of Sciences and the National Academy of Engineering, and a Fellow of the American Academy of Arts and Sciences.

For more information, please visit the UCI Department of Computer Science Distinguished Lecture Series.