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

IF 0.5 4区 数学 Q4 SOCIAL SCIENCES, MATHEMATICAL METHODS Journal of Official Statistics Pub Date : 2023-09-01 DOI:10.2478/jos-2023-0019
K. Muralidhar, J. Domingo-Ferrer
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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:: :”.
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对Garfinkel(2023)的回复-保护2020年十年一次的美国人口普查的遗留统计披露限制技术:仍然是一个可行的选择
在我们的文章“数据库重建不是那么容易,不同于重新识别”中,我们表明可以通过适当使用传统的统计披露控制(SDC)技术来避免重建,有时也称为遗留统计披露限制(SDL)技术。此外,我们还指出,即使重建可以进行,它并不意味着重新识别。因此,重建的风险似乎不能保证用基于差分隐私(DP)的保护取代传统的SDC技术。在西姆森·加芬克尔(Simson Garfinkel)的《传统统计披露限制技术不是2020年美国人口和住房普查的选择》一书中,作者坚持认为,2020年人口普查转向DP是合理的。在我们看来,后一篇文章包含了一些误解,我们将在下面识别并详细讨论这些误解。因此,我们支持“数据库重建不是那么容易:::”中给出的论点。
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来源期刊
Journal of Official Statistics
Journal of Official Statistics STATISTICS & PROBABILITY-
CiteScore
1.90
自引率
9.10%
发文量
39
审稿时长
>12 weeks
期刊介绍: JOS is an international quarterly published by Statistics Sweden. We publish research articles in the area of survey and statistical methodology and policy matters facing national statistical offices and other producers of statistics. The intended readers are researchers or practicians at statistical agencies or in universities and private organizations dealing with problems which concern aspects of production of official statistics.
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