Privacy-Preserving Data Publishing

Bee Chung Chen, Daniel Kifer, Kristen LeFevre, Ashwin Machanavajjhala

Research output: Contribution to journalArticle

100 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)1-167
Number of pages167
JournalFoundations and Trends in Databases
Volume2
Issue number1-2
DOIs
StatePublished - Dec 31 2009

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

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