Privacy in Statistical Databases: UNESCO Chair in Data Privacy, International Conference, PSD 2014, Ibiza, Spain, September 17-19, 2014. Proceedings

Author:   Josep Domingo-Ferrer
Publisher:   Springer International Publishing AG
Edition:   2014 ed.
Volume:   8744
ISBN:  

9783319112565


Pages:   367
Publication Date:   23 September 2014
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Privacy in Statistical Databases: UNESCO Chair in Data Privacy, International Conference, PSD 2014, Ibiza, Spain,  September 17-19, 2014. Proceedings


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Overview

This book constitutes the refereed proceedings of the International Conference on Privacy in Statistical Databases, PSD 2014, held in Ibiza, Spain in September 2014 under the sponsorship of the UNESCO chair in Data Privacy. The 27 revised full papers presented were carefully reviewed and selected from 41 submissions. The scope of the conference is on following topics: tabular data protection, microdata masking, protection using privacy models, synthetic data, record linkage, remote access, privacy-preserving protocols, and case studies.

Full Product Details

Author:   Josep Domingo-Ferrer
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   2014 ed.
Volume:   8744
Dimensions:   Width: 15.50cm , Height: 2.00cm , Length: 23.50cm
Weight:   5.737kg
ISBN:  

9783319112565


ISBN 10:   3319112562
Pages:   367
Publication Date:   23 September 2014
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Tabular Data Protection.- Enabling Statistical Analysis of Suppressed Tabular Data.- Assessing the Information Loss of Controlled Adjustment Methods in Two-Way Tables.- Further Developments with Perturbation Techniques to Protect Tabular Data.- Comparison of Different Sensitivity Rules for Tabular Data and Presenting a New Rule – The Interval Rule.- Pre-tabular Perturbation with Controlled Tabular Adjustment: Some Considerations.- Measuring Disclosure Risk with Entropy in Population Based Frequency Tables.- A CTA Model Based on the Huber Function.- Microdata Masking Density Approximant Based on Noise Multiplied Data.- Reverse Mapping to Preserve the Marginal Distributions of Attributes in Masked Microdata .- JPEG-Based Microdata Protection.- Protection Using Privacy Models.- Improving the Utility of Differential Privacy via Univariate Microaggregation.- Differentially Private Exponential Random Graphs.- km-Anonymity for Continuous Data Using Dynamic Hierarchies.- Differentially-Private Logistic Regression for Detecting Multiple-SNP Association in GWAS Databases.- Synthetic Data.- Disclosure Risk Evaluation for Fully Synthetic Categorical Data.- v-Dispersed Synthetic Data Based on a Mixture Model with Constraints.- Nonparametric Generation of Synthetic Data for Small Geographic Areas.- Using Partially Synthetic Data to Replace Suppression in the Business Dynamics Statistics: Early Results.- Synthetic Longitudinal Business Databases for International Comparisons .- Record Linkage.- A Comparison of Blocking Methods for Record Linkage.- Probabilistic Record Linkage for Disclosure Risk Assessment.- Hierarchical Linkage Clustering with Distributions of Distances for Large-Scale Record Linkage.- Remote Access.- Comparison of Two Remote Access Systems Recently Developed and Implemented in Australia.- Privacy-Preserving Protocols.- Towards Secure and Practical Location Privacy through Private Equality Testing.- Case Studies.- Controlled Shuffling, StatisticalConfidentiality and Microdata Utility: A Successful Experiment with a 10% Household Sample of the 2011 Population Census of Ireland for the IPUMS-International Database.- Balancing Confidentiality and Usability: Protecting Sensitive Data in the Case of Inward Foreign AffiliaTes Statistics (FATS).- Applicability of Confidentiality Methods to Personal and Business Data.

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