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Privacy in Statistical Databases

UNESCO Chair in Data Privacy, International Conference, PSD 2018, Valencia, Spain, September 26–28, 2018, Proceedings

  • Conference proceedings
  • © 2018

Overview

Editors:
  1. Josep Domingo-Ferrer

    1. Rovira i Virgili University, Tarragona, Spain

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    You can also search for this editor in PubMed   Google Scholar

  2. Francisco Montes

    1. University of Valencia, Burjassot, Spain

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11126)

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 2018.

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Table of contents (23 papers)

  1. Front Matter

    Pages I-XI
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  2. Tabular Data Protection

    1. Front Matter

      Pages 1-1
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    2. Symmetric vs Asymmetric Protection Levels in SDC Methods for Tabular Data

      • Daniel Baena, Jordi Castro, José A. González
      Pages 3-12

    3. Bounded Small Cell Adjustments for Flexible Frequency Table Generators

      • Min-Jeong Park
      Pages 13-27

    4. Designing Confidentiality on the Fly Methodology – Three Aspects

      • Tobias Enderle, Sarah Giessing, Reinhard Tent
      Pages 28-42

    5. Protecting Census 2021 Origin-Destination Data Using a Combination of Cell-Key Perturbation and Suppression

      • Iain Dove, Christos Ntoumos, Keith Spicer
      Pages 43-55

  3. Synthetic Data

    1. Front Matter

      Pages 57-57
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    2. On the Privacy Guarantees of Synthetic Data: A Reassessment from the Maximum-Knowledge Attacker Perspective

      • Nicolas Ruiz, Krishnamurty Muralidhar, Josep Domingo-Ferrer
      Pages 59-74

    3. The Quasi-Multinomial Synthesizer for Categorical Data

      • Jingchen Hu, Nobuaki Hoshino
      Pages 75-91

    4. Synthetic Data via Quantile Regression for Heavy-Tailed and Heteroskedastic Data

      • Michelle Pistner, Aleksandra Slavković, Lars Vilhuber
      Pages 92-108

    5. Some Clarifications Regarding Fully Synthetic Data

      • Jörg Drechsler
      Pages 109-121

    6. Differential Correct Attribution Probability for Synthetic Data: An Exploration

      • Jennifer Taub, Mark Elliot, Maria Pampaka, Duncan Smith
      Pages 122-137

    7. pMSE Mechanism: Differentially Private Synthetic Data with Maximal Distributional Similarity

      • Joshua Snoke, Aleksandra Slavković
      Pages 138-159

    8. The Application of Genetic Algorithms to Data Synthesis: A Comparison of Three Crossover Methods

      • Yingrui Chen, Mark Elliot, Duncan Smith
      Pages 160-171

  4. Microdata and Big Data Masking

    1. Front Matter

      Pages 173-173
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    2. Multiparty Computation with Statistical Input Confidentiality via Randomized Response

      • Josep Domingo-Ferrer, Rafael Mulero-Vellido, Jordi Soria-Comas
      Pages 175-186

    3. Grouping of Variables to Facilitate SDL Methods in Multivariate Data Sets

      • Anna Oganian, Ionut Iacob, Goran Lesaja
      Pages 187-199

    4. Comparative Study of the Effectiveness of Perturbative Methods for Creating Official Microdata in Japan

      • Shinsuke Ito, Toru Yoshitake, Ryo Kikuchi, Fumika Akutsu
      Pages 200-214

    5. A General Framework and Metrics for Longitudinal Data Anonymization

      • Nicolas Ruiz
      Pages 215-230

    6. Reviewing the Methods of Estimating the Density Function Based on Masked Data

      • Yan-Xia Lin, Pavel N. Krivitsky
      Pages 231-246
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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 2018, held in Valencia, Spain, in September 2018 under the sponsorship of the UNESCO Chair in Data Privacy.

The 23 revised full papers presented were carefully reviewed and selected from 42 submissions. The papers are organized into the following topics: tabular data protection; synthetic data; microdata and big data masking; record linkage; and spatial and mobility data.

Chapter "SwapMob: Swapping Trajectories for Mobility Anonymization" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Editors and Affiliations

  • Rovira i Virgili University, Tarragona, Spain

    Josep Domingo-Ferrer

  • University of Valencia, Burjassot, Spain

    Francisco Montes

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