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Privacy in Statistical Databases

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Cover of 'Privacy in Statistical Databases'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 p % Should Dominate
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    Chapter 2 A Computational Evaluation of Optimization Solvers for CTA
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    Chapter 3 Flexible Rounding Based on Consistent Post-tabular Stochastic Noise
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    Chapter 4 Comparing L 1 and L 2 Distances for CTA
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    Chapter 5 An Investigation of Model-Based Microdata Masking for Magnitude Tabular Data Release
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    Chapter 6 Testing of IHSN C++ Code and Inclusion of New Methods into sdcMicro
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    Chapter 7 Clustering-Based Categorical Data Protection
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    Chapter 8 Anonymization Methods for Taxonomic Microdata
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    Chapter 9 Hybrid Microdata via Model-Based Clustering
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    Chapter 10 Logistic Regression with Variables Subject to Post Randomization Method
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    Chapter 11 Valid Statistical Inference on Automatically Matched Files
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    Chapter 12 n -Cycle Swapping for the American Community Survey
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    Chapter 13 Generating Useful Test Data for Complex Linked Employer-Employee Datasets
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    Chapter 14 When Excessive Perturbation Goes Wrong and Why IPUMS-International Relies Instead on Sampling, Suppression, Swapping, and Other Minimally Harmful Methods to Protect Privacy of Census Microdata
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    Chapter 15 Achieving Comparability of Earnings
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    Chapter 16 Designing Multiple Releases from the Small and Medium Enterprises Survey
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    Chapter 17 A Proposed Solution to the Archiving and Curation of Confidential Scientific Inputs
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    Chapter 18 Confidentialising Maps of Mixed Point and Diffuse Spatial Data
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    Chapter 19 Security of Random Output Perturbation for Statistical Databases
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    Chapter 20 Empirical Evaluation of Statistical Inference from Differentially-Private Contingency Tables
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    Chapter 21 Differentially Private Graphical Degree Sequences and Synthetic Graphs
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    Chapter 22 European Data Access Comes True
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    Chapter 23 A Bayesian Approach for On-Line Sum/Count/Max/Min Auditing on Boolean Data
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    Chapter 24 Document Sanitization: Measuring Search Engine Information Loss and Risk of Disclosure for the Wikileaks cables
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    Chapter 25 Enhancing the Efficiency in Privacy Preserving Learning of Decision Trees in Partitioned Databases
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    Chapter 26 On Computational Anonymity
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    Chapter 27 ”Better Than Nothing” Privacy with Bloom Filters: To What Extent?
Attention for Chapter 19: Security of Random Output Perturbation for Statistical Databases
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Chapter title
Security of Random Output Perturbation for Statistical Databases
Chapter number 19
Book title
Privacy in Statistical Databases
Published by
Springer, Berlin, Heidelberg, September 2012
DOI 10.1007/978-3-642-33627-0_19
Book ISBNs
978-3-64-233626-3, 978-3-64-233627-0
Authors

Daniel Z. Zanger

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 1 100%
Readers by discipline Count As %
Computer Science 1 100%