Step-by-step guide to building and deploying AI and ML models for industrial IoT and WSN security enables hands-on learning and application
Focus on real-world attack detection and anomaly analysis equips readers with practical skills for threat identification
Comprehensive exploration of the full data science lifecycle from data collection to model deployment ensures a complete learning experience
Practical Python code for visualization, attack simulation, and decision-making supports hands-on experimentation
Coverage of future trends such as edge AI, federated learning, and zero trust security keeps readers ahead of emerging threats
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While the Industrial Internet of Things (IIoT) and Wireless Sensor Networks (WSNs) continue to redefine industrial infrastructure, the need for proactive, intelligent, and scalable cybersecurity solutions has never been more pressing. This book provides a hands-on, research-driven guide t