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Link to original content: https://doi.org/10.1007/978-3-031-02347-7
Database Anonymization: Privacy Models, Data Utility, and Microaggregation-based Inter-model Connections | SpringerLink
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Database Anonymization

Privacy Models, Data Utility, and Microaggregation-based Inter-model Connections

  • Book
  • © 2016

Overview

Authors:
  1. Josep Domingo-Ferrer

    1. Universitat Rovira i Virgili, Tarragona, Catalonia, Spain

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  2. David Sánchez

    1. Universitat Rovira i Virgili, Tarragona, Catalonia, Spain

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    You can also search for this author in PubMed   Google Scholar

  3. Jordi Soria-Comas

    1. Universitat Rovira i Virgili, Tarragona, Catalonia, Spain

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About this book

The current social and economic context increasingly demands open data to improve scientific research and decision making. However, when published data refer to individual respondents, disclosure risk limitation techniques must be implemented to anonymize the data and guarantee by design the fundamental right to privacy of the subjects the data refer to. Disclosure risk limitation has a long record in the statistical and computer science research communities, who have developed a variety of privacy-preserving solutions for data releases. This Synthesis Lecture provides a comprehensive overview of the fundamentals of privacy in data releases focusing on the computer science perspective. Specifically, we detail the privacy models, anonymization methods, and utility and risk metrics that have been proposed so far in the literature. Besides, as a more advanced topic, we identify and discuss in detail connections between several privacy models (i.e., how to accumulate the privacy guaranteesthey offer to achieve more robust protection and when such guarantees are equivalent or complementary); we also explore the links between anonymization methods and privacy models (how anonymization methods can be used to enforce privacy models and thereby offer ex ante privacy guarantees). These latter topics are relevant to researchers and advanced practitioners, who will gain a deeper understanding on the available data anonymization solutions and the privacy guarantees they can offer.

Table of contents (11 chapters)

  1. Front Matter

    Pages i-xv
    Download chapter PDF

  2. Introduction

    • Josep Domingo-Ferrer, David Sánchez, Jordi Soria-Comas
    Pages 1-2

  3. Privacy in Data Releases

    • Josep Domingo-Ferrer, David Sánchez, Jordi Soria-Comas
    Pages 3-13

  4. Anonymization Methods for Microdata

    • Josep Domingo-Ferrer, David Sánchez, Jordi Soria-Comas
    Pages 15-23

  5. Quantifying Disclosure Risk: Record Linkage

    • Josep Domingo-Ferrer, David Sánchez, Jordi Soria-Comas
    Pages 25-29

  6. The k-Anonymity Privacy Model

    • Josep Domingo-Ferrer, David Sánchez, Jordi Soria-Comas
    Pages 31-45

  7. Beyond k-Anonymity: l-Diversity and t-Closeness

    • Josep Domingo-Ferrer, David Sánchez, Jordi Soria-Comas
    Pages 47-51

  8. t-Closeness Through Microaggregation

    • Josep Domingo-Ferrer, David Sánchez, Jordi Soria-Comas
    Pages 53-63

  9. Differential Privacy

    • Josep Domingo-Ferrer, David Sánchez, Jordi Soria-Comas
    Pages 65-77

  10. Differential Privacy by Multivariate Microaggregation

    • Josep Domingo-Ferrer, David Sánchez, Jordi Soria-Comas
    Pages 79-95

  11. Differential Privacy by Individual Ranking Microaggregation

    • Josep Domingo-Ferrer, David Sánchez, Jordi Soria-Comas
    Pages 97-103

  12. Conclusions and Research Directions

    • Josep Domingo-Ferrer, David Sánchez, Jordi Soria-Comas
    Pages 105-108

  13. Back Matter

    Pages 109-120
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Authors and Affiliations

  • Universitat Rovira i Virgili, Tarragona, Catalonia, Spain

    Josep Domingo-Ferrer, David Sánchez, Jordi Soria-Comas

About the authors

Josep Domingo-Ferrer received an M.Sc. and a Ph.D. in computer science from the Autonomous University of Barcelona in 1988 and 1991, respectively. He also received an M.Sc. degree in mathematics. He is a Distinguished Professor of Computer Science and an ICREA-Acadèmia researcher at the Universitat Rovira i Virgili, Tarragona, Catalonia, where he holds the UNESCO Chair in Data Privacy. His research interests are in data privacy, data security, and cryptographic protocols. He is a Fellow of IEEE.David Sánchez received a Ph.D. in computer science from the Technical University of Catalonia. He also received an M.Sc. degree in computer science from the Universitat Rovira i Virgili, Tarragona, Catalonia, in 2003, where he is currently an Associate Professor of Computer Science. His research interests are in data semantics and data privacyJordi Soria-Comas received a B.Sc. degree in mathematics from the University of Barcelona in 2003, and an M.Sc. degree in finance from the Autonomous University of Barcelona in 2004. He received an M.Sc. degree in computer security in 2011, and a Ph.D. in computer science in 2013 from the Universitat Rovira i Virgili. He is a Director of Research at Universitat Rovira i Virgili. His research interests are in data privacy and security

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