On the Benefits of Sampling in Privacy Preserving Statistical Analysis on Distributed Databases

Understand

We consider a problem where mutually untrusting curators possess portions of a vertically partitioned database containing information about a set of individuals.

• The goal is to enable an authorized party to obtain aggregate (statistical) information from the database while protecting the privacy of the individuals, which we formalize using Differential Privacy.
• This process can be facilitated by an untrusted server that provides storage and processing services but should not learn anything about the database.
• This work describes a data release mechanism that employs Post Randomization (PRAM), encryption and random sampling to maintain privacy, while allowing the authorized party to conduct an accurate statistical analysis of the data.