Database Anonymization : Privacy Models, Data Utility, and Microaggregation-based Inter-model Connections / by Josep Domingo-Ferrer, David Sánchez, Jordi Soria-Comas.

Format:

Book

Author/Creator:

Domingo-Ferrer, Josep., Author.

Sánchez, David., Author.

Soria-Comas, Jordi., Author.

Series:

Synthesis Lectures on Information Security, Privacy, and Trust, 1945-9750

Language:

English

Subjects (All):

Data protection.

Data and Information Security.

Local Subjects:

Data and Information Security.

Physical Description:

1 online resource (XV, 120 p.)

Edition:

1st ed. 2016.

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2016.

Summary:

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 guarantees they 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.

Contents:

Preface

Acknowledgments

Introduction

Privacy in Data Releases

Anonymization Methods for Microdata

Quantifying Disclosure Risk: Record Linkage

The k-Anonymity Privacy Model

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

t-Closeness Through Microaggregation

Differential Privacy

Differential Privacy by Multivariate Microaggregation

Differential Privacy by Individual Ranking Microaggregation

Conclusions and Research Directions

Bibliography

Authors' Biographies .

ISBN:

9783031023477

3031023471