Private and Continual Release of Statistics

Abstract

We ask the question: how can Web sites 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 Web sites to continually give top- k and hot items suggestions while preserving users’ privacy.

Document Details

Document Type
Pub Defense Publication
Publication Date
Nov 01, 2011
Source ID
10.1145/2043621.2043626

Entities

People

  • Dawn Song
  • Elaine Shi
  • T.-h. Hubert Chan

Organizations

  • Division of Computing and Communication Foundations
  • Office of Naval Research
  • PARC
  • University of California, Berkeley
  • University of Hong Kong

Tags

Fields of Study

  • Computer science
  • Mathematics

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Database Systems and Applications