Analysis of the Kim-Winkler Algorithm for Masking Microdata Files : How Much Masking Is Necessary and Sufficient Conjectures for the Development of a Controllable Algorithm

By Moore, Richard A.

Book Id: WPLBN0000579599
Format Type: PDF eBook:
File Size: 0.1 MB
Reproduction Date: 2005

Title:	Analysis of the Kim-Winkler Algorithm for Masking Microdata Files : How Much Masking Is Necessary and Sufficient Conjectures for the Development of a Controllable Algorithm
Author:	Moore, Richard A.
Volume:
Language:	English
Subject:	Government publications, Census., Census report
Collections:	Government Library Collection, U.S. Census Bureau Collection
Historic Publication Date:
Publisher:	United States Census Bureau Department


Citation APA MLA Chicago A. Moor, B. R. (n.d.). Analysis of the Kim-Winkler Algorithm for Masking Microdata Files : How Much Masking Is Necessary and Sufficient Conjectures for the Development of a Controllable Algorithm. Retrieved from http://gutenberg.cc/

Description
Statistical Reference Document

Excerpt
Excerpt: In 1995, the Bureau of the Census supplemented 59,315 records from the March 1991 Current Population Survey (CPS) with income fields for each household. It obtained values for these incomes from administrative records provided by the Internal Revenue Service (IRS). The resulting microdata file was then to be released to the Department of Health and Human Services (HHS), so that it might set policy for earned income and other benefits. Having access to the actual microdata (and not just summary statistics), HHS would be able to make better decisions.

Table of Contents
Table of Contents Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 pages Chapters I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 II. Purpose of This Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 III. The Technique for the Measurement of the Amount of Masking Provided . . . . . . . . . . . 3 IV. Masking By the Addition of Random Noise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 V. The Test Deck and the Generation of Random Noise . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Table 1. Statistics for the Fields Subjected to the Addition of Random Noise . . . . 5 Table 2. Statistics for the Random Noise For c = 0.100 . . . . . . . . . . . . . . . . . . . . 5 Table 3. Correlation Coefficients Before and After the Addition of Random Noise For c =0.1005 (R = 0.99) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 0 VI. The Masking Ability of Kim?s Technique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Table 4. Ability of Kim?s Addition of Random Noise to Mask Data ... . . . . . . . . . 7 VII. The Value Where c Loses Its Effectiveness, Mathematical Conjectures . . . . . . . . . . . . . 9 Table 5. Theoretical Value at Which c Loses Its Masking Power . . . . . . . . . . . . . 9 VIII. The Advantages and Disadvantages of Kim?s Masking Technique . . . . . . . . . . . . . . . . 11 IX. Winkler?s Matching Software, An Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 X. The Advantages and Disadvantages of a Swap Procedure . . . . . . . . . . . . . . . . . . . . . . . 13 XI. Conjecture for a Re-Identification Tolerance Level, Historical Evidence . . . . . . . . . . . . 14 XII. Using Winkler?s Approach to Achieve Re-Identification Tolerance . . . . . . . . . . . . . . . . 16 XIII. Conjecture on an Optimal Masking Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 XIV. Future Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17