A Rejoinder to Garfinkel (2023) – Legacy Statistical Disclosure Limitation Techniques for Protecting 2020 Decennial US Census: Still a Viable Option

Author:

Muralidhar Krishnamurty1,Domingo-Ferrer Josep2

Affiliation:

1. 1 University of Oklahoma , Price College of Business, Dept. of Marketing and Supply Chain Management , 307 West Brooks, Adams Hall Room 10, Norman, OK 73019 , U.S.A .

2. 2 Universitat Rovira i Virgili , Dept. of Computer Engineering and Mathematics, CYBERCAT-Center for Cybersecurity Research of Catalonia , Av. Països Catalans 26, 43007 Tarragona , Catalonia , Spain .

Abstract

Abstract In our article “Database Reconstruction Is Not So Easy and Is Different from Reidentification”, we show that reconstruction can be averted by properly using traditional statistical disclosure control (SDC) techniques, also sometimes called legacy statistical disclosure limitation (SDL) techniques. Furthermore, we also point out that, even if reconstruction can be performed, it does not imply reidentification. Hence, the risk of reconstruction does not seem to warrant replacing traditional SDC techniques with differential privacy (DP) based protection. In “Legacy Statistical Disclosure Limitation Techniques Were Not an Option for the 2020 US Census of Population and Housing”, by Simson Garfinkel, the author insists that the 2020 Census move to DP was justified. In our view, this latter article contains some misconceptions that we identify and discuss in some detail below. Consequently, we stand by the arguments given in “Database Reconstruction Is Not So Easy:: :”.

Publisher

SAGE Publications

Subject

Statistics and Probability

Reference20 articles.

1. Abowd, J.M. 2021. Declaration of John M. Abowd. Case no. 3:21-CV-211-RAH-ECM-KCN, U.S. District Court for the Middle District of Alabama. Available at: https://censusproject.files.wordpress.com/2021/04/2021.04.13-abowd-declaration-alabama-v.-commerce-ii-final-signed.pdf.

2. Abowd, J., R. Ashmead, R. Cumings-Menon, S. Garfinkel, M. Heineck, C. Heiss, and R. Johns. 2022. “The 2020 Census Disclosure Avoidance System TopDown Algorithm.” Harvard Data Science Review 2. Available at: https://hdsr.mitpress.mit.edu/pub/7evz361i (accessed May 2023).

3. Abowd, J.M., G.L. Benedetto, S.L. Garfinkel, S.A. Dahl, A.N. Dajani, M. Graham, and M.B. Hawes. 2020. The Modernization of Statistical Disclosure Limitation at the U.S. Census Bureau. Available at: https://www.census.gov/library/working-papers/2020/adrm/CED-WP-2020-009.html (accessed May 2023).

4. Bach, F. 2022. “Differential Privacy and Noisy Confidentiality Concepts for European Population Statistics.” Journal of Survey Statistics and Methodology, 10: 642–687. DOI: https://doi.org/10.1093/jssam/smab044.

5. Dajani, A.N., A.D. Lauger, P.E. Singer, D. Kifer, J.P. Reiter, A., Machanavajjhala, S.L. Garfinkel, S.A. Dahl, M. Graham, V. Karwa, H. Kim, P. Leclerc, I.M. Schmutte, W.N. Sexton, L. Vilhuber, and J.M. Abowd. 2017. “The modernization of statistical disclosure limitation at the U.S. Census Bureau.” In: Census Scientific Advisory Committee Meeting, September 14 – 15, Suitland MD, USA. Available at: https://www.census.gov/library/video/2017/2017-09-sac.html (accessed May 2023).

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