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

Muralidhar Krishnamurty () and Domingo-Ferrer Josep ()
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Muralidhar Krishnamurty: 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.
Domingo-Ferrer Josep: 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.

Journal of Official Statistics, 2023, vol. 39, issue 3, 411-420

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:: :”.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:offsta:v:39:y:2023:i:3:p:411-420:n:8

DOI: 10.2478/jos-2023-0019

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