Private and Continual Release of Statistics

by 

Hubert Chan
HKU

Time: 11am on Friday, April 30, 2010
Venue: 3530

Abstract:
We ask the question -- how can websites and data aggregators
continually release updated
statistics, and meanwhile preserve each individual user's privacy?
Suppose we are given a stream of 0's and 1's. We propose a
differentially private continual counter that outputs
at every time step the approximate number of 1's seen thus far. Our
counter construction has error that is only poly-log in the number of
time steps. We can extend the basic counter construction to allow
websites to continually give top-k and hot items suggestions while
preserving users' privacy.

This is joint work with Elaine Shi and Dawn Song.