About this book:

*IoT Security in the Age of AI* explores the critical intersection of ubiquitous connectivity and advanced analytics, providing a comprehensive framework for defending the expanding Internet of Things (IoT) ecosystem. The book highlights how traditional security perimeters are insufficient for heterogeneous, resource-constrained devices that often operate in harsh environments for decades. It argues that a successful defense must integrate a "secure-by-design" philosophy at the manufacturing level—utilizing hardware roots of trust and secure boot—with a "never trust, always verify" Zero Trust architecture during operation.

The core of the text focuses on the synergy between edge intelligence and cloud-scale analytics. By deploying lightweight AI models directly on devices and gateways, operators can achieve real-time anomaly detection and preserve data privacy through techniques like federated and split learning. These localized defenses are complemented by cloud-scale data lakes and processing pipelines that normalize and enrich telemetry with global threat intelligence. This dual approach allows for the detection of sophisticated threats, such as lateral movement and supply chain tampering, that would be invisible to isolated devices.

Beyond technical implementation, the book details the operational lifecycle of IoT security, covering secure over-the-air (OTA) update orchestration, certificate management, and incident response for distributed fleets. It emphasizes the importance of model governance to ensure AI defenders remain unbiased and effective against evolving adversarial tactics. Through various case studies in manufacturing, healthcare, energy, and smart cities, the text demonstrates how these strategies satisfy rigorous safety, privacy, and regulatory compliance mandates like GDPR and HIPAA.

Looking forward, the author anticipates a transition toward "AI-native" defenses, where self-healing and self-orchestrating systems manage security with minimal human intervention. As emerging challenges like quantum computing and complex supply chain vulnerabilities arise, the book advocates for standardized security baselines and digital product passports. Ultimately, the work serves as a practical guide for engineers and leaders to transform vulnerable connected machines into resilient, intelligent assets capable of defending themselves in an increasingly hostile digital landscape.

What You'll Find Inside:

• Learn how hardware roots of trust, secure boot, and firmware signing establish an immutable chain of trust from silicon to software.
• Discover techniques for protecting the IoT supply chain using Software Bills of Materials (SBOMs), attestations, and hardened factory provisioning.
• Master lightweight AI model design (quantization, pruning, knowledge distillation) for real-time threat detection on constrained edge devices.
• Understand how federated and split learning enable privacy‑preserving collaborative model training across device fleets without exposing raw data.
• Explore Zero Trust principles for IoT—strong device identity, least‑privilege policies, and micro‑segmentation—to contain lateral movement and enforce continuous verification.

Who's It For:

This book is intended for IoT engineers, solution architects, product managers, and security practitioners who are responsible for designing, deploying, or defending connected device ecosystems. It will benefit those seeking practical, patterns‑based guidance on integrating edge intelligence, cloud analytics, and zero‑trust principles to secure devices across manufacturing, healthcare, energy, and smart‑city environments.