Data Privacy: Foundations, New Developments and the Big Data Challenge

This book offers a broad, cohesive overview of the field of data privacy. It discusses, from a technological perspective, the problems and solutions of the three main communities working on data privacy: statistical disclosure control (those with a statistical background), privacy-preserving data mining (those working with data bases and data mining), and privacy-enhancing technologies (those involved in communications and security) communities.

Presenting different approaches, the book describes alternative privacy models and disclosure risk measures as well as data protection procedures for respondent, holder and user privacy. It also discusses specific data privacy problems and solutions for readers who need to deal with big data.

Table of Contents

Chapter 1 Introduction
Chapter 2 Machine And Statistical Learning
Chapter 3 On The Classification Of Protection Procedures
Chapter 4 User’S Privacy
Chapter 5 Privacy Models And Disclosure Risk Measures
Chapter 6 Masking Methods
Chapter 7 Information Loss: Evaluation And Measures
Chapter 8 Selection Of Masking Methods
Chapter 9 Conclusions