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Privacy in Statistical Databases

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

  • Conference proceedings
  • © 2014

Overview

Editors:
  1. Josep Domingo-Ferrer

    1. Department of Computer Engineering and Mathematics, UNESCO Chair in Data Privacy, Universitat Rovira i Virgili, Tarragona, Catalonia

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 8744)

Part of the book sub series: Information Systems and Applications, incl. Internet/Web, and HCI (LNISA)

Included in the following conference series:

Conference proceedings info: PSD 2014.

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Table of contents (28 papers)

  1. Front Matter

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  2. Tabular Data Protection

    1. Enabling Statistical Analysis of Suppressed Tabular Data

      • Lawrence H. Cox
      Pages 1-10

    2. Assessing the Information Loss of Controlled Adjustment Methods in Two-Way Tables

      • Jordi Castro, José A. González
      Pages 11-23

    3. Further Developments with Perturbation Techniques to Protect Tabular Data

      • María-Salomé Hernández-García, Juan-José Salazar-González
      Pages 24-35

    4. Comparison of Different Sensitivity Rules for Tabular Data and Presenting a New Rule – The Interval Rule

      • Johan Bring, Qun Wang
      Pages 36-47

    5. Pre-tabular Perturbation with Controlled Tabular Adjustment: Some Considerations

      • Sarah Giessing
      Pages 48-61

    6. Measuring Disclosure Risk with Entropy in Population Based Frequency Tables

      • Laszlo Antal, Natalie Shlomo, Mark Elliot
      Pages 62-78

    7. A CTA Model Based on the Huber Function

      • Jordi Castro
      Pages 79-88

  3. Microdata Masking

    1. Density Approximant Based on Noise Multiplied Data

      • Yan-Xia Lin
      Pages 89-104

    2. Reverse Mapping to Preserve the Marginal Distributions of Attributes in Masked Microdata

      • Krishnamurty Muralidhar, Rathindra Sarathy, Josep Domingo-Ferrer
      Pages 105-116

    3. JPEG-Based Microdata Protection

      • Javier Jiménez, Guillermo Navarro-Arribas, Vicenç Torra
      Pages 117-129

  4. Protection Using Privacy Models

    1. Improving the Utility of Differential Privacy via Univariate Microaggregation

      • David Sánchez, Josep Domingo-Ferrer, Sergio Martínez
      Pages 130-142

    2. Differentially Private Exponential Random Graphs

      • Vishesh Karwa, Aleksandra B. Slavković, Pavel Krivitsky
      Pages 143-155

    3. k m-Anonymity for Continuous Data Using Dynamic Hierarchies

      • Olga Gkountouna, Sotiris Angeli, Athanasios Zigomitros, Manolis Terrovitis, Yannis Vassiliou
      Pages 156-169

    4. Differentially-Private Logistic Regression for Detecting Multiple-SNP Association in GWAS Databases

      • Fei Yu, Michal Rybar, Caroline Uhler, Stephen E. Fienberg
      Pages 170-184

  5. Synthetic Data

    1. Disclosure Risk Evaluation for Fully Synthetic Categorical Data

      • Jingchen Hu, Jerome P. Reiter, Quanli Wang
      Pages 185-199

    2. v-Dispersed Synthetic Data Based on a Mixture Model with Constraints

      • Anna Oganian
      Pages 200-212

    3. Nonparametric Generation of Synthetic Data for Small Geographic Areas

      • Joseph W. Sakshaug, Trivellore E. Raghunathan
      Pages 213-231

    4. Using Partially Synthetic Data to Replace Suppression in the Business Dynamics Statistics: Early Results

      • Javier Miranda, Lars Vilhuber
      Pages 232-242

    5. Synthetic Longitudinal Business Databases for International Comparisons

      • Jörg Drechsler, Lars Vilhuber
      Pages 243-252
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Other volumes

  1. Privacy in Statistical Databases

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About this book

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.

Editors and Affiliations

  • Department of Computer Engineering and Mathematics, UNESCO Chair in Data Privacy, Universitat Rovira i Virgili, Tarragona, Catalonia

    Josep Domingo-Ferrer

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