Berkman Luncheon Series >
28
2010
I'm in the Database, but Nobody Knows
Cynthia Dwork, Microsoft Research
Tuesday, September 28, 12:30 pm
Berkman Center, 23 Everett
Street, second floor
RSVP required for those
attending in person (rsvp@cyber.law.harvard.edu)
This
event will be webcast
live
at 12:30 pm ET and archived on our site shortly after.
Co-hosted by Harvard's Center for Research on Computation and Society
A statistical database provides statistical information about a
population, while maintaining the privacy of individuals in the
database. A popular interpretation of this statement, due to Dalenius,
says that "anything learnable about an individual, given access to the
database, can be learned without access to the database." In
non-technical terms, we will discuss why any such definition is
problematic, and suggest an alternate notion of privacy for statistical
databases, differential privacy, that arises naturally from an
observation about the impossibility argument.
A thriving research effort has produced high-quality differentially
private solutions for a wide range of data analysis tasks. We will try
to give a feel for the broad spectrum of things that can be done by
accessing information through a privacy-preserving programming
interface. Finally, we will touch on some privacy problems arising in
the context of behavioral targeting that are not addressed by this
approach, and pose some questions about mitigation.
About Cynthia
Cynthia Dwork, a theoretical computer scientist, has made fundamental contributions to cryptography, distributed computing, and complexity theory. Her current focus is the development of a mathematically rigorous framework and algorithmic techniques for the privacy-preserving analysis of data. A Distinguished Scientist at Microsoft, Dwork is a recipient of the Edsger W. Dijkstra Prize and a member of the US National Academy of Engineering and the American Academy of Arts and Sciences.
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Last updated October 05, 2010