Producing accurate, usable data while protecting respondent privacy are dual mandates of the US Census Bureau. In 2019, the Census Bureau announced it would use a new disclosure avoidance technique, based on differential privacy, for the 2020 Decennial Census of Population and Housing. Instead of suppressing data or swapping sensitive records, differentially private methods inject noise into counts to protect privacy. Unfortunately, noise injection may also make the data less useful and accurate. This paper describes the differentially private Disclosure Avoidance System (DAS) used to prepare the 2010 Demonstration Data Product (DDP). It describes the policy decisions that underlie the DAS and how the DAS uses those policy decisions to produce differentially private data. Finally, it discusses usability and accuracy issues in the DDP, with a focus on occupied housing unit counts. Occupied housing unit counts in the DDP differed greatly from 2010 Summary File 1 differed greatly, and the paper explains possible sources of the differences.
|Original language||English (US)|
|Title of host publication||Privacy in Statistical Databases - UNESCO Chair in Data Privacy, International Conference, PSD 2020, Proceedings|
|Editors||Josep Domingo-Ferrer, Krishnamurty Muralidhar|
|Publisher||Springer Science and Business Media Deutschland GmbH|
|Number of pages||16|
|State||Published - 2020|
|Event||International Conference on Privacy in Statistical Databases, PSD 2020 - Tarragona, Spain|
Duration: Sep 23 2020 → Sep 25 2020
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||International Conference on Privacy in Statistical Databases, PSD 2020|
|Period||9/23/20 → 9/25/20|
Bibliographical noteFunding Information:
Supported by the Minnesota Population Center (R24 HD041023), funded through grants from the Eunice Kennedy Shriver National Institute for Child Health and Human Development.
© 2020, Springer Nature Switzerland AG.
- 2020 US Decennial Census
- Differential privacy