Formal Privacy At Scale: The 2020 Decennial Census TopDown Disclosure Limitation Algorithm

To control vulnerabilities to reconstruction-abetted re-identification attacks that leverage massive external data stores and cheap computation, the U.S. Census Bureau has elected to adopt a formally private approach to disclosure limitation in the 2020 Decennial Census of Population and Housing. To this end, a team of disclosure limitation specialists have worked over the past 3 years to design and implement the U.S. Census Bureau TopDown Disclosure Limitation Algorithm (TDA). This formally private algorithm generates Persons and Households micro-data, which will then be tabulated to produce the final set of demographic statistics published as a result of the 2020 Census enumeration. In this talk, I outline the main features of TDA, describe the current iteration of the process used to help policy makers decide how to set and allocate privacy-loss budget, and outline known issues with - and intended fixes for - the current implementation of TDA.