Noise Infusion As A Confidentiality Protection Measure For Graph-Based Statistics
We use the bipartite graph representation of longitudinally linked em-ployer-employee data, and the associated projections onto the employer and em-ployee nodes, respectively, to characterize the set of potential statistical summar-ies that the trusted custodian might produce. We consider noise infusion as the primary confidentiality protection method. We show that a relatively straightfor-ward extension of the dynamic noise-infusion method used in the U.S. Census Bureau’s Quarterly Workforce Indicators can be adapted to provide the same confidentiality guarantees for the graph-based statistics: all inputs have been modified by a minimum percentage deviation (i.e., no actual respondent data are used) and, as the number of entities contributing to a particular statistic increases, the accuracy of that statistic approaches the unprotected value. Our method also ensures that the protected statistics will be identical in all releases based on the same inputs.
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- John M. Abowd & Bryce E. Stephens & Lars Vilhuber & Fredrik Andersson & Kevin L. McKinney & Marc Roemer & Simon Woodcock, 2009.
"The LEHD Infrastructure Files and the Creation of the Quarterly Workforce Indicators,"
NBER Chapters,in: Producer Dynamics: New Evidence from Micro Data, pages 149-230
National Bureau of Economic Research, Inc.
- John M. Abowd & Bryce E. Stephens & Lars Vilhuber & Fredrik Andersson & Kevin L. McKinney & Marc Roemer & Simon Woodcock, 2002. "The LEHD Infrastructure Files and the Creation of the Quarterly Workforce Indicators," Longitudinal Employer-Household Dynamics Technical Papers 2002-05, Center for Economic Studies, U.S. Census Bureau.
- John Abowd & Bryce Stephens & Lars Vilhuber, 2006. "The LEHD Infrastructure Files and the Creation of the Quarterly Workforce Indicators," Longitudinal Employer-Household Dynamics Technical Papers 2006-01, Center for Economic Studies, U.S. Census Bureau.
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