Abstract
In 2017, the United States Census Bureau announced that because of high disclosure risk in the methodology (data swapping) used to produce tabular data for the 2010 census, a different protection mechanism based on differential privacy would be used for the 2020 census. While there have been many studies evaluating the result of this change, there has been no rigorous examination of disclosure risk claims resulting from the released 2010 tabular data. In this study we perform such an evaluation. We show that the procedures used to evaluate disclosure risk are unreliable and resulted in inflated disclosure risk. Demonstration data products released using the new procedure were also shown to have poor utility. However, since the Census Bureau had already committed to a different procedure, they had no option except to escalate their commitment. The result of such escalation is that the 2020 tabular data release offers neither privacy nor accuracy.
Original language | English (US) |
---|---|
Title of host publication | Privacy in Statistical Databases - International Conference, PSD 2024, Proceedings |
Editors | Josep Domingo-Ferrer, Melek Önen |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 393-402 |
Number of pages | 10 |
ISBN (Print) | 9783031696503 |
DOIs | |
State | Published - 2024 |
Event | International Conference on Privacy in Statistical Databases, PSD 2024 - Antibes Juan-les-Pins, France Duration: Sep 25 2024 → Sep 27 2024 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
---|---|
Volume | 14915 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | International Conference on Privacy in Statistical Databases, PSD 2024 |
---|---|
Country/Territory | France |
City | Antibes Juan-les-Pins |
Period | 9/25/24 → 9/27/24 |
Bibliographical note
Publisher Copyright:© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Keywords
- Census
- disclosure
- privacy