Mastering Secure Data Anonymization and Pseudonymization: A Comprehensive Framework for Privacy and Compliance in the Digital Age

Mastering Secure Data Anonymization and Pseudonymization: A Comprehensive Framework for Privacy and Compliance in the Digital Age
Author :
Publisher : Libertatem Media Private Limited
Total Pages : 222
Release :
ISBN-10 : 9788197138294
ISBN-13 : 819713829X
Rating : 4/5 (29X Downloads)

Book Synopsis Mastering Secure Data Anonymization and Pseudonymization: A Comprehensive Framework for Privacy and Compliance in the Digital Age by : Sumanth Tatineni

Download or read book Mastering Secure Data Anonymization and Pseudonymization: A Comprehensive Framework for Privacy and Compliance in the Digital Age written by Sumanth Tatineni and published by Libertatem Media Private Limited. This book was released on 2024-03-29 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book delves into the innovative framework for data anonymization and pseudonymization designed to safeguard Personally Identifiable Information (PII) in an era of heightened data privacy concerns and regulatory requirements. With the rapid growth of digital data and stringent regulations like GDPR and HIPAA, organizations face an urgent need to protect sensitive information without sacrificing its utility. Drawing from a patent-pending framework, this book offers a deep exploration into the methodologies, technologies, and applications of secure data handling practices. It provides readers with a step-by-step understanding of the framework's components, including machine learning-based PII detection, advanced anonymization techniques, and controlled re-identification processes. Through real-world examples, practical applications, and insights into regulatory compliance, this book equips professionals, researchers, and policymakers with the knowledge and tools needed to navigate the complexities of data privacy. Readers will gain a comprehensive understanding of how to implement secure data anonymization and pseudonymization, ensuring both privacy and operational efficiency, and learn how to integrate these practices seamlessly into existing data management workflows.


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