Data Privacy: Building Blocks, Latest Advancements, and the Challenge of Big Data

Data Privacy: Building Blocks, Latest Advancements, and the Challenge of Big Data offers a comprehensive and timely exploration of how privacy is managed, protected, and challenged in the age of massive data generation. With digital systems deeply embedded in our daily lives, this textbook unpacks the foundational principles of data privacy while addressing cutting-edge developments and real-world applications.

From core concepts and privacy legislation to the impact of machine learning and the complexities introduced by Big Data, each chapter builds a layered understanding of privacy frameworks. Readers will explore GDPR compliance, data masking techniques, classification models, and ethical considerations—all while learning how innovation and privacy can coexist.

The book also addresses critical topics such as privacy in healthcare, algorithmic transparency, and performance metrics for data analytics, offering tools to both evaluate and enhance data protection practices. A real-world case study in Big Data forensics ties theory to application, preparing readers for practical challenges.

Ideal for students, researchers, and professionals in IT, cybersecurity, and data science, this book is a clear, accessible guide to mastering privacy in a rapidly evolving digital world.