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Building an Anonymization Pipeline
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Building an Anonymization Pipeline
by Khaled El Emam, Luk Arbuckle
Building an Anonymization Pipeline
Preface
Audience
Conventions Used in This Book
Using Code Examples
O’Reilly Online Learning
How to Contact Us
Acknowledgments
1. Introduction
Our Motivation in Writing This Book
Getting to Terms
Regulations
States of Data
Anonymization as Data Protection
Approval or Consent
Purpose Specification
Re-Identification Attacks
Risk-Based Anonymization
About This Book
2. Identifiability Spectrum
Legal Landscape
Disclosure Risk
Types of Disclosure
Dimensions of Data Privacy
Re-Identification Science
Defined Population
Direction of Matching
Structure of Data
Re-Identification Risk
Final Thoughts
3. A Practical Risk-Management Framework
Five Safes of Anonymization
Safe Projects
Safe People
Safe Settings
Safe Data
Safe Outputs
Five Safes in Practice
Final Thoughts
4. Identified Data
Requirements Gathering
Use Cases
Data Flows
Data and Data Subjects
From Primary to Secondary Use
Dealing with Direct Identifiers
Dealing with Indirect Identifiers
From Identified to Anonymized
Mixing Identified with Anonymized
Applying Anonymized to Identified
Final Thoughts
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Building an Anonymization Pipeline
Building an Anonymization Pipeline
Luk Arbuckle and Khaled El Emam
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