Work with interactive mapping tools from across the Census Bureau.
Read briefs and reports from Census Bureau experts.
Watch Census Bureau vignettes, testimonials, and video files.
Read research analyses from Census Bureau experts.
Developer portal to access services and documentation for the Census Bureau's APIs.
Explore Census Bureau data on your mobile device with interactive tools.
Find a multitude of DVDs, CDs and publications in print by topic.
These external sites provide more data.
Download extraction tools to help you get the in-depth data you need.
Explore Census data with interactive visualizations covering a broad range of topics.
Information about the U.S. Census Bureau.
Information about what we do at the U.S. Census Bureau.
Learn about other opportunities to collaborate with us.
Explore the rich historical background of an organization with roots almost as old as the nation.
Explore prospective positions available at the U.S. Census Bureau.
Information about the current field vacancies available at the U.S. Census Bureau Regional Offices.
Discover the latest in Census Bureau data releases, reports, and events.
The Census Bureau's Director writes on how we measure America's people, places and economy.
Find interesting and quirky statistics regarding national celebrations and major events.
Find media toolkits, advisories, and all the latest Census news.
See what's coming up in releases and reports.
Government agencies collect many types of data, but due to confidentiality restrictions, use of the microdata is
often limited to sworn agents working on secure computer systems at those agencies. These restrictions can
severely affect public policy decisions made at one agency that has access to nonconfidential summary statistics
only. This necessitates creation of microdata which not only meets the confidentiality requirements but also has
sufficient utility. This paper describes a general methodology for producing public-use data files that preserves
confidentiality and allows many analytical uses. The methodology masks quantitative data using an additive-noise
approach and then, when necessary, employs a reidentification/swapping methodology to assure confidentiality.
One of the major advantages of this masking scheme is that it also allows obtaining precise subpopulation estimates,
which is not possible with other known masking schemes. In addition, if controlled distortion is applied, then a
prespecified subset of subpopulation estimates from the masked file could be nearly identical to those from the
unmasked file. This paper provides the theoretical underpinning of the masking methodology and the results of its
actual application using examples.