AI Agents for Secure and Software-Defined Networking: Harnessing AI and SDN to Revolutionize Modern Work Environments

AI agents for modern, secure networking

AI Agents for Secure and Software-Defined Networking: Harnessing AI and SDN to Revolutionize Modern Work Environments brings artificial intelligence into the center of network design, operations, and defense. Het Mehta structures the material around a practical question: how can networked systems become more adaptive, more autonomous, and more resilient without losing control, visibility, or security?

This is a deeply technical book, but it is organized with clear progression. It begins with AI-agent architectures and decentralized network management, then moves through intent-based networking, federated learning, cross-layer orchestration, digital twins, cognitive healing, policy management, autonomous traffic engineering, ethical AI, threat intelligence, and multi-tenant resource allocation. That sequence gives the book a strong engineering logic: each chapter builds another piece of the larger case for AI-driven networking.

What the book covers

• AI agents in network management and orchestration
• Intent-based networking and adaptive policy control
• Federated learning and collaborative optimization
• Digital twins for simulation, testing, and planning
• Cognitive network healing and proactive remediation
• Reinforcement learning for traffic engineering
• Threat intelligence, response, and responsible governance

Who it speaks to

The table of contents and publisher description point to a readership of network architects, engineers, security practitioners, researchers, and technically minded decision-makers. Readers looking for a broad but detailed overview of AI-enabled networking will find the book especially relevant if they want to connect automation, policy, performance, and security in one place.

For anyone following the shift from manually managed networks to software-defined, AI-assisted infrastructure, this ebook offers a coherent map of the field and a useful set of ideas to return to as systems grow more complex.