The Complete Book of Data Anonymization: From Planning to Implementation, 1st Edition (Hardback) book cover

The Complete Book of Data Anonymization

From Planning to Implementation, 1st Edition

By Balaji Raghunathan

Auerbach Publications

267 pages | 95 B/W Illus.

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Hardback: 9781439877302
pub: 2013-05-21
eBook (VitalSource) : 9780429188282
pub: 2013-05-21
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The Complete Book of Data Anonymization: From Planning to Implementation supplies a 360-degree view of data privacy protection using data anonymization. It examines data anonymization from both a practitioner's and a program sponsor's perspective. Discussing analysis, planning, setup, and governance, it illustrates the entire process of adapting and implementing anonymization tools and programs.

Part I of the book begins by explaining what data anonymization is. It describes how to scope a data anonymization program as well as the challenges involved when planning for this initiative at an enterprisewide level.

Part II describes the different solution patterns and techniques available for data anonymization. It explains how to select a pattern and technique and provides a phased approach towards data anonymization for an application.

A cutting-edge guide to data anonymization implementation, this book delves far beyond data anonymization techniques to supply you with the wide-ranging perspective required to ensure comprehensive protection against misuse of data.


With more and more regulations focusing on protection of data privacy and prevention of misuse of personal data, anonymization of sensitive data is becoming a critical need for corporate and governmental organizations. This book provides a comprehensive view of data anonymization both from a program sponsor’s perspective as well as a practitioner’s. The special focus on implementation of data anonymization across the enterprise makes this a valuable reference book for large data anonymization implementation programs.

Prasad Joshi, Vice President, Infosys Labs, Infosys Ltd.

This book on data anonymization could not have come at a better time, given the rapid adoption of outsourcing within enterprises and an ever increasing growth of business data. This book is a must read for enterprise data architects and data managers grappling with the problem of balancing the needs of application outsourcing with the requirements for strong data privacy.

Dr. Pramod Varma, Chief Architect, Unique Identification Authority of India

Table of Contents

Overview of Data Anonymization

Points to Ponder



What is Data Anonymization?

What are the Drivers for Data Anonymization?

The Need To Protect Sensitive Data Handled As Part Of Business

Increasing Instances of Insider Data Leakage, Misuse of Personal Data and the Lure of Money for Mischievous Insiders

Employees Getting Even With Employers

Negligence of Employees to Sensitivity of Personal Data

Astronomical Cost to the Business due to Misuse of Personal Data

Risks Arising out of Operational Factors Like Outsourcing and Partner Collaboration

Outsourcing Of IT Application Development, Testing And Support

Increasing Collaboration With Partners

Legal and Compliance Requirements

Will Procuring and Implementing a Data Anonymization Tool by Itself Ensure Protection of Privacy of Sensitive Data?

Ambiguity of Operational Aspects

Allowing the Same Users to Access both Masked and Unmasked Environment

Lack Of Buy-In From IT Application Developers, Testers and End-Users

Compartmentalized Approach to Data Anonymization

Absence of Data Privacy Protection Policies or Weak enforcement of Data Privacy Policies

Benefits Of Data Anonymization Implementation


Enterprise Data Privacy Governance Model

Points to Ponder

Chief Privacy Officer

Unit /Department Privacy Compliance Officers

The Steering Committee for Data Privacy Protection Initiatives

Management Representatives

Information Security And Risk Department Representatives

Representatives from the Department Security and Privacy Compliance Officers

Incident Response Team

The Role of the Employee in Privacy Protection

The Role of the CIO

Typical Ways Enterprises Enforce Privacy Policies

Enterprise Data Classification Policy and Privacy Laws

Points to Ponder

Regulatory Compliance

Enterprise Data Classification

Points to Consider

Controls For Each Class Of Enterprise Data

Operational Processes, Guidelines and Controls for Enterprise Data Privacy Protection

Points to Ponder

Privacy Incident Management

Planning for Incident Resolution


Incident Capture

Incident Response

Post Incident Analysis

Guidelines and Best Practices

PII/PHI Collection Guidelines

Guidelines for Storage and Transmission of PII/PHI

PII/PHI Usage Guidelines

Guidelines for Storing PII/PHI on Portable Devices and Storage Devices

Guidelines for Staff

The Different Phases of a Data Anonymization Program

Points to Ponder

How Should I Go about the Enterprise Data Anonymization Program?

The Assessment Phase

Tool Evaluation and Solution Definition Phase

Data Anonymization Implementation Phase

Operations Phase or the Steady-State phase

Food For Thought

When Should the Organization Invest on a Data Anonymization Exercise?

The Organization’s Security Policies Anyway Mandate Authorization to be Built-in For Every Application. Won’t This be Sufficient? Why is Data Anonymization Needed?

Is there a Business Case for Data Anonymization Program in My Organization?

When Can a Data Anonymization Program be Called as a Successful One?

Why Should I go for a Data Anonymization Tool when SQL Encryption Scripts Can be Used to Anonymize Data?

What are the Benefits Provided by Data Masking Tools for Data Anonymization?

Why is a Tool Evaluation Phase Needed?

Who Should Implement Data Anonymization? Should it be the Tool Vendor or the IT Service Partner or External Consultants or Internal Employees?

How Many Rounds of Testing Must be Planned to Certify that Application Behavior is Unchanged with use of Anonymized Data?

Departments Involved in Enterprise Data Anonymization Program

Points to Ponder

The Role of the Information Security and Risk Department

The Role of the Legal Department

The Role of Application Owners and Business Analysts

The Role of Administrators

The Role of the Project Management Office (PMO)

The Role of the Finance department

Steering Committee

Privacy Meter- Assessing The Maturity Of Data Privacy Protection Practices In The Organization

Points to Ponder

Planning A Data Anonymization Implementation

Data Privacy Maturity Model

Enterprise Data Anonymization Execution Model

Points to Ponder

Decentralized Model

Centralized Anonymization Setup

Shared Services Model

Tools and Technology

Points to Ponder

Shortlisting Tools for Evaluation

Tool Evaluation and Selection

Functional Capabilities

Technical Capabilities

Operational Capabilities

Financial Parameters

Scoring criteria for Evaluation

Anonymization Implementation – Activities & Effort

Points to Ponder

Anonymization Implementation Activities For An Application

Application Anonymization Analysis and Design

Anonymization Environment Setup

Application Anonymization Configuration and Build

Anonymized Application Testing

Complexity Criteria

Application Characteristics

Environment Dependencies

Arriving at an Effort Estimation Model

Definition of Complexity Criteria

Ready-Reckoner Preparation

Determination Of The Complexity Of The Application To Be Anonymized

Assignment of Effort to Each Activity Based on the Ready-Reckoner

Case Study


Estimation Approach

Application Complexity

Arriving at a Ball Park Estimate

The Next Wave of Data Privacy Challenges


Data Anonymization Patterns

Points to Ponder

Pattern Overview

Data State Anonymization Patterns

Points to Ponder

Principles of Anonymization

Static Masking Patterns

EAL Pattern (Extract Anonymize Load Pattern)

ELA Pattern (Extract Load Anonymize Pattern)

Data Subsetting

Dynamic Masking

Dynamic Masking Patterns

Interception Pattern

Invocation Patterns

Application of Dynamic Masking patterns

Dynamic Masking vs. Static Masking

Anonymization Environment Patterns

Points to Ponder

Typical Application Environments in an enterprise

Testing Environments

Standalone Environment

Integration Environment

Automated Integration Test environment

Scaled-Down Integration Test Environment

Data Flow Patterns Across Environments

Points to Ponder

Flow of Data from Production Environment Databases to Non-Production Environment Databases

Movement of Anonymized Files from Production Environment to Non-Production Environments

Masked Environment for Integration Testing-Case Study

Data Anonymization Techniques

Points to Ponder

Basic Anonymization Techniques



Number Variance

Date Variance

Nulling Out

Character Masking

Cryptographic Techniques

Partial Sensitivity and Partial Masking

Masking Based on External Dependency

Auxiliary Anonymization Techniques

Alternate Classification of Data Anonymization Techniques

Substitution Techniques

Translation Techniques

Leveraging Data Anonymization Techniques

Data Anonymization Implementation

Points to Ponder

Pre-Requisites Before Starting The Anonymization Implementation Activities

Sensitivity Definition Readiness - What is Considered as Sensitive Data by the Organization?

Sensitive Data Discovery- Where does Sensitive Data Exist?

Application Architecture Analysis

Application Sensitivity Analysis

What is Sensitivity Level and How Do We Prioritize Sensitive Fields for Treatment?

Anonymization Design Phase

Anonymization Implementation, Testing, and Rollout Phase

Anonymization Operations

Incorporation of Privacy protection procedures as part of Software Development Life Cycle and Application Lifecycle for New Applications

Impact on SDLC Team

Challenges Faced as part of Any Data Anonymization Implementation

Best Practices To Ensure Success Of Anonymization Projects


About the Author

Balaji Raghunathan has more than 20 years of experience in the software industry. As part of his current role as General Manager, Technology Consulting & Enterprise Architecture, at ITC Infotech, Balaji Raghunathan is responsible for helping the clients of ITC Infotech simplify their technology landscape, assess their readiness for digital initiatives, modernize their technology architecture and prepare them for their digital journey

Balaji Raghunathan has also lead the delivery of digital projects for banking, financial services, and insurance customers as well as helped them define their digital strategy. He has lead strategy engagements for enterprise mobility initiatives as well as developed, managed and commercialized intellectual property (IP) during his prior stints with Capgemini and Infosys. During the last decade, Balaji Raghunathan has been involved in architecting software solutions for the energy, utilities, publishing, transportation, retail, and banking industries

Balaji Raghunathan’s core areas of interest revolves around digital technology strategy, data privacy management and enterprise mobility. He is an avid blogger on Digital Technology Strategy, and has authored the book "The Complete Book of Data Anonymization-From Planning to Implementation". He has also the co-authored a chapter "Mobility and Its Impact on Enterprise Security" for the book "Information Security Management Handbook, Sixth Edition, Volume 7."

He holds a patent on "System and Method for Runtime Data Anonymization" and has a pending patent on "System and Method for categorization of Social Media Conversation for Response Management."

He is a TOGAF 8.0 and ICMG-WWISA Certified Software Architect.

Balaji Raghunathan has a postgraduate diploma in business administration (finance) from Symbiosis Institute (SCDL), Pune, India and has an engineering degree (electrical and electronics) from Bangalore University, India. He has also completed a Senior Leadership Certificate course from Indian Institute of Management, Kozhikode.

About the Series

Infosys Press

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Subject Categories

BISAC Subject Codes/Headings:
COMPUTERS / Information Technology
COMPUTERS / Software Development & Engineering / General
COMPUTERS / Security / General