Differential privacy in the 2020 US census: what will it do? Quantifying the accuracy/privacy tradeoff.

ABSTRACT: Background: The 2020 US Census will use a novel approach to disclosure avoidance to protect respondents' data, called TopDown. This TopDown algorithm was applied to the 2018 end-to-end (E2E) test of the decennial census. The computer code used for this test as well as accompanying exposition has recently been released publicly by the Census Bureau. Methods: We used the available code and data to better understand the error introduced by the E2E disclosure avoidance system when Census Bureau applied it to 1940 census data and we developed an empirical measure of privacy loss to compare the error and privacy of the new approach to that of a (non-differentially private) simple-random-sampling approach to protecting privacy. Results: We found that the empirical privacy loss of TopDown is subst

SUBMITTER: Petti S 

PROVIDER: S-EPMC7216402 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature