Description

Data is now the fuel of every industry, from healthcare and automotive to smart homes and AI‑powered services. As connected devices, cloud platforms, and machine learning spread everywhere, privacy and security risks silently grow alongside innovation.

Guided by real‑world scenarios, the book moves from the origins of data privacy and regulatory frameworks to practical data classification, anonymization, and masking techniques you can implement. You will learn how automation, AI, and ML interact with privacy; how blockchain can both enhance and endanger data protection; how to secure IoT ecosystems and healthcare data; and how to manage privacy in automotive and smart mobility, including attack tools such as Flipper Zero. Finally, you will build a unifying privacy framework that ties together standards, governance, and hands‑on controls across all these domains.

By the end of this book, readers will be able to analyze and classify data, design and evaluate privacy controls. They will be equipped to translate privacy principles into concrete architectures, policies, and safeguards that make a measurable difference in their daily work, whatever their sector.