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The Census TopDown Algorithm (TDA) is a disclosure avoidance system using differential privacy for privacy-loss accounting.
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Donald. Rubin · 1974
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“Public Law 94-171”
94th Congress · 1975
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“k-anonymity: A Model for Protecting Privacy”
Latanya Sweeney · 2002
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“Revealing Information While Preserving Privacy”
Irit Dinur and Kobbi Nissim · 2003
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“The Discrete Gaussian for Differential Privacy”
Clément. Canonne, Gautam Kamath and Thomas Steinke · 2004
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“Preserving the Confidentiality of Categorical Statistical Databases when Releasing Information for Association Rules”
Stephen Fienberg and Aleksandra Slavkovic · 2005
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“Our Data, Ourselves: Privacy Via Distributed Noise Generation”
Cynthia Dwork et al · 2006
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“Calibrating Noise to Sensitivity in Private Data Analysis”
Cynthia Dwork, Frank McSherry, Kobbi Nissim and Adam. Smith · 2006
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“AOL Removes Search Data on Group of Web Users New York Times”
S Hansell · 2006
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“Mechanism Design via Differential Privacy”
Frank McSherry and Kunal Talwar · 2007
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“Minimality Attack in Privacy Preserving Data Publishing”
Raymond-Wing Wong, Ada-Chee Fu, Ke Wang and Jian Pei · 2007
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“Resolving Individuals Contributing Trace Amounts of DNA to Highly Complex Mixtures Using High-Density SNP Genotyping Microarrays”
Nils Homer et al · 2008
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Ashwin Machanavajjhala et al · 2008
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“Robust De-anonymization of Large Datasets (How to Break Anonymity of the Netflix Prize Dataset)”
Arvind Narayanan and Vitaly Shmatikov · 2008
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“On The Map: Longitudinal Employer-Household Dynamics”
U.S. Census Bureau · 2008
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“Public Law 111-117”
111th Congress · 2009
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“Attacks on Privacy and deFinetti’s Theorem”
Daniel Kifer · 2009
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“Privacy Integrated Queries: An Extensible Platform for Privacy-preserving Data Analysis”
Frank McSherry · 2009
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“A Statistical Framework for Differential Privacy”
Larry Wasserman and Shuheng Zhou · 2010
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“The ‘Re-identification’ of Governor William Weld’s Medical Information: a Critical Re-examination of Health Data Identification Risks and Privacy Protections”
Daniel Barth-Jones · 2012
Cited alongside, same era.
“Universally Utility-Maximizing Privacy Mechanisms”
Arpita Ghosh, Tim Roughgarden and Mukund Sundararajan · 2012
Cited alongside, same era.
“On Significance of the Least Significant Bits for Differential Privacy”
Ilya Mironov · 2012
Cited alongside, same era.
“Quality and the 2010 Census”
Howard Hogan et al · 2013
“Disclosure Avoidance Techniques Used for the 1970 through 2010 Decennial Censuses of Population and Housing”
Laura McKenna · 2018
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“An act to add Title 1.81.5 (commencing with Section 1798.100) to Part 4 of Division 3 of the Civil Code, relating to privacy ”
State of California · 2018
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“An Economic Analysis of Privacy Protection and Statistical Accuracy as Social Choices”
John. Abowd and Ian. Schmutte · 2019
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“Differential Privacy on Finite Computers”
Victor Balcer and Salil Vadhan · 2019
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“Disclosure Avoidance Techniques Used for the 1960 Through 2010 Decennial Censuses of Population and Housing Public Use Microdata Samples”
Laura McKenna · 2019
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Cited alongside, same era.
“The Algorithmic Foundations of Differential Privacy”
Cynthia Dwork and Aaron Roth · 2014
Cited alongside, same era.
“RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response”
Úlfar Erlingsson, Vasyl Pihur and Aleksandra Korolova · 2014
Cited alongside, same era.
“On the ‘Semantics’ of Differential Privacy: A Bayesian Formulation”
Shiva Kasiviswanathan and Adam Smith · 2014
Cited alongside, same era.
“Economic Analysis and Statistical Disclosure Limitation”
John. Abowd and Ian. Schmutte · 2015
Cited alongside, same era.
“De-identification of Personal Information”
Simson. Garfinkel · 2015
Cited alongside, same era.
“The Composition Theorem for Differential Privacy”
Peter Kairouz, Sewoong Oh and Pramod Viswanath · 2015
Cited alongside, same era.
“A Better Bound Gives a Hundred Rounds: Enhanced Privacy Guarantees via f-Divergences” Funding Information: This work was supported in part by NSF under grants CIF 1922971, 1815361, 1742836, 1900750, and CIF CAREER 1845852. Publisher Copyright: © 2020 IEEE.; 2020 IEEE International Symposium on Information Theory, ISIT 2020 ; Conference date: 21-07-2020 Through 26-07-2020
Shahab Asoodeh et al · 2020
Later among the works it cites.
“Hypothesis Testing Interpretations and Renyi Differential Privacy”
Borja Balle et al · 2020
Later among the works it cites.
“The Discrete Gaussian for Differential Privacy”
Clément Canonne, Gautam Kamath and Thomas Steinke · 2020
Later among the works it cites.
“Linear Program Reconstruction in Practice”
Aloni Cohen and Kobbi Nissim · 2020
Later among the works it cites.
“Randomness Concerns When Deploying Differential Privacy”
Simson. Garfinkel and Philip Leclerc · 2020
Later among the works it cites.
“Counting for Dollars 2020: The Role of the Decennial Census in the Geographic Distribution of Federal Funds”
Andrew Reamer · 2020
Later among the works it cites.
“Private Posterior Inference Consistent with Public Information: A Case Study in Small Area Estimation from Synthetic Census Data”
Jeremy Seeman, Aleksandra Slavkovic and Matthew Reimherr · 2020
Later among the works it cites.
“Formal Privacy Methods for the 2020 Census”
The JASON Group · 2020
Later among the works it cites.
“2020 Census Data Products Crosswalk”
U.S. Census Bureau · 2020
Later among the works it cites.
“Data Metrics for 2020 Disclosure Avoidance: November 16, 2020 release”
U.S. Census Bureau · 2020
Later among the works it cites.
“An Uncertainty Principle is a Price of Privacy-Preserving Microdata”
John. Abowd et al · 2021
Later among the works it cites.
“Geographic Spines in the 2020 Census Disclosure Avoidance System Topdown Algorithm”
John. Abowd et al · 2021
Later among the works it cites.
“Gaussian Differential Privacy”
Jinshuo Dong, Aaron Roth and Weijie Su · 2021
Later among the works it cites.
“Redistricting Criteria”
National Conference of State Legislatures · 2021
Later among the works it cites.
“2020 Census Redistricting Data (Public Law (P.L.) 94-171) Summary File – United States machine-readable data files/prepared by the U.S. Census Bureau, 2021.”, 2021
U.S. Census Bureau · 2021
Later among the works it cites.
“DAS 2020 Redistricting Production Code Release”
U.S. Census Bureau · 2021
Later among the works it cites.
“Data Metrics for 2020 Disclosure Avoidance: Update for the April 28, 2021 release”
U.S. Census Bureau · 2021
Later among the works it cites.
“Developing the DAS: Demonstration Data and Progress Metrics” Accessed: 2022-01-15, 2021
U.S. Census Bureau · 2021
Later among the works it cites.
“Empirical Study of Two Aspects of the TopDown Algorithm Output for Redistricting: Reliability & Variability”
Tommy Wright and Kyle Irimata · 2021
Later among the works it cites.
“Simulation Studies to Investigate Variation in Census Counts and in Census Coverage Error Using 2010 SF-1 Data and 2010 CCM Results”
William Bell and Joseph Schafer · 2022
Closest in time.
“Understanding Disclosure Avoidance-Related Variability in the 2020 Census Redistricting Data”
U.S. Census Bureau · 2022
Closest in time.