Privacy-Preserving Data Publishing

Bee-Chung Chen
Yahoo! Research

Daniel Kifer
Penn State University

Kristen LeFevre
University of Michigan

Ashwin Machanavajjhala
Yahoo! Research

SUGGESTED CITATION:
Bee-Chung Chen, Daniel Kifer, Kristen LeFevre and Ashwin Machanavajjhala (2009) "Privacy-Preserving Data Publishing",
Foundations and Trends® in Databases: Vol. 2: No 1-2, pp 1-167.
http://dx.doi.org/10.1561/1900000008

Abstract

Privacy is an important issue when one wants to make use of data that involves individuals' sensitive information. Research on protecting the privacy of individuals and the confidentiality of data has received contributions from many fields, including computer science, statistics, economics, and social science. In this paper, we survey research work in privacy-preserving data publishing. This is an area that attempts to answer the problem of how an organization, such as a hospital, government agency, or insurance company, can release data to the public without violating the confidentiality of personal information. We focus on privacy criteria that provide formal safety guarantees, present algorithms that sanitize data to make it safe for release while preserving useful information, and discuss ways of analyzing the sanitized data. Many challenges still remain. This survey provides a summary of the current state of the art, based on which we expect to see advances in years to come.