Introduction

Explainable AI for Secure and Transparent AIoT Blockchain Integration explores the convergence of AIoT, Explainable AI (XAI), Blockchain and cybersecurity to build intelligent systems that are secure, transparent and accountable. As AIoT expands into healthcare, smart cities, agriculture, transportation and energy, the book tackles data tampering, device spoofing, privacy breaches, adversarial attacks and opaque AI decisions moving from foundational AIoT-XAI-Blockchain integration through security challenges, advanced machine learning (deep learning, federated learning, intrusion detection) next-generation approaches (Graph Neural Networks, TinyML, zero-trust architectures) and future directions in edge AI and lightweight cryptography.

Key Features

• - Integration of AIoT, XAI, and Blockchain for secure decision-making.
• - Coverage of real-world security breaches and authentication methods.
• - Advanced ML: federated learning, intrusion detection, quantum-resistant security.
• - Next-gen approaches: Graph Neural Networks, TinyML, zero-trust architectures.
• - Forward-looking discussion of ethical and regulatory considerations.

Readership :

Researchers, postgraduate students, cybersecurity professionals, and AI/IoT developers; secondarily, policymakers and industry professionals.