ABSTRACT

Gaining access to high-quality data is a vital necessity in knowledge-based decision making. But data in its raw form often contains sensitive information about individuals. Providing solutions to this problem, the methods and tools of privacy-preserving data publishing enable the publication of useful information while protecting data privacy. Int

part 1|2 pages

Part I: The Fundamentals

chapter 1|10 pages

Introduction

chapter 2|22 pages

Attack Models and Privacy Models

chapter 3|8 pages

Anonymization Operations

chapter 4|6 pages

Information Metrics

chapter 5|18 pages

Anonymization Algorithms

part 2|2 pages

Part II: Anonymization for Data Mining

chapter 6|36 pages

Anonymization for Classification Analysis

chapter 7|24 pages

Anonymization for Cluster Analysis

part 3|2 pages

Part III: Extended Data Publishing Scenarios

part 4|2 pages

Part IV: Anonymizing Complex Data

chapter 13|32 pages

Anonymizing Transaction Data

chapter 14|30 pages

Anonymizing Trajectory Data

chapter 15|14 pages

Anonymizing Social Networks

chapter 16|8 pages

Sanitizing Textual Data