This book provides a structured, practical exploration of modern computer networking concepts and the transformative role of artificial intelligence in cybersecurity. This book begins by introducing the foundational principles of computer networks, networking models, protocols, and architectures, together with essential concepts of artificial intelligence. Building on these fundamentals, it examines the evolving cyber threat landscape and explains how AI-driven techniques enhance threat detection, prevention, and response against contemporary attacks, such as phishing, ransomware, and zero-day exploits. It also covers secure networking practices, containerization, automated configuration management, and the role of automation in building resilient infrastructures.

Subsequent chapters focus on advanced and applied topics, including Infrastructure as Code, DevSecOps integration, ethical hacking, penetration testing, incident response, and AI-assisted threat hunting. Emerging areas such as zero-trust networking, IoT security, large-scale enterprise deployments, and future trends in AI-powered cybersecurity are also discussed. Emphasis is placed on hands-on learning through labs, case studies, and real-world scenarios, supported by an accompanying GitHub repository.

Designed for students and educators, this book bridges theoretical understanding with practical skills required for modern, AI-driven cyber defense environments. Professionals, network administrators, and cybersecurity practitioners interested in AI-driven security and modern network will also find this book useful as a reference.

Structured hands-on laboratories integrating computer networks, AI, and cybersecurity workflows Companion GitHub repository supporting reproducible experiments and applied learning Industry-aligned content designed to enhance professional readiness and certification pathways

Autorentext

Islom Mamatov is a Security and Cloud Infrastructure Architect with a background in Computer Science and a strong focus on digital transformation in higher education. He has led multiple institutional projects, including university automation systems, registrar platforms, and cloud-based admissions solutions. His research interests span computer networks, cloud infrastructure security, artificial intelligence, and cybersecurity, with particular emphasis on generative AI applications in education and phishing attack detection. He is also the author of Smart Networking: Learning Computer Networks with AI Tools, a pedagogical work designed to help students master networking concepts through AI-enabled learning methodologies.

Mohammad Gouse Galety is a Professor in the School of Computing at Samarkand International University of Technology, Uzbekistan. His research in computer and information science encompasses web mining, computer vision, the Internet of Things, machine learning, and artificial intelligence. His scholarly work has resulted in multiple patents, authored and edited books, and a substantial body of peer-reviewed journal articles and international conference publications, indexed in major academic databases including Springer, Web of Science, and Scopus. His professional standing is further reinforced through his affiliations with IEEE and ACM. He has accumulated extensive academic and professional experience spanning more than two decades across a wide range of national and international institutions, including Sree Vidyanikethan Degree College and Brindavan College of Engineering in India; Emeralds Degree College, Tirupati; Kuwait Educational Center, Kuwait; Ambo University and Debre Berhan University in Ethiopia; Lebanese French University, Iraq; and the Catholic University in Erbil, Iraq. He teaches computer science and information technology–related engineering programs at both undergraduate and postgraduate levels.

Arul Kumar Natarajan is an Assistant Professor in the School of Computing at Samarkand International University of Technology, Uzbekistan. He earned his doctoral degree in Computer Science from Bharathidasan University, India, and has extensive teaching experience across leading academic institutions in India, Ethiopia, and Uzbekistan. His research focuses on cybersecurity and artificial intelligence, with a substantial record of peer-reviewed journal publications, conference presentations, and edited scholarly books indexed in Scopus. He also has several forthcoming books with internationally reputed publishers, including IGI Global, Wiley, and Springer. A prolific innovator, he holds multiple patents granted in India and the United Kingdom, as well as a government-copyrighted project in artificial intelligence and machine learning. He has earned professional certifications from Cisco and Microsoft, demonstrating strong expertise in networking and cybersecurity, and continues to pursue advanced research at the intersection of generative artificial intelligence and cybersecurity.

Klappentext

This book provides a structured, practical exploration of modern computer networking concepts and the transformative role of artificial intelligence in cybersecurity. This book begins by introducing the foundational principles of computer networks, networking models, protocols, and architectures, together with essential concepts of artificial intelligence. Building on these fundamentals, it examines the evolving cyber threat landscape and explains how AI-driven techniques enhance threat detection, prevention, and response against contemporary attacks, such as phishing, ransomware, and zero-day exploits. It also covers secure networking practices, containerization, automated configuration management, and the role of automation in building resilient infrastructures.

Subsequent chapters focus on advanced and applied topics, including Infrastructure as Code, DevSecOps integration, ethical hacking, penetration testing, incident response, and AI-assisted threat hunting. Emerging areas such as zero-trust networking, IoT security, large-scale enterprise deployments, and future trends in AI-powered cybersecurity are also discussed. Emphasis is placed on hands-on learning through labs, case studies, and real-world scenarios, supported by an accompanying GitHub repository.

Designed for students and educators, this book bridges theoretical understanding with practical skills required for modern, AI-driven cyber defense environments. Professionals, network administrators, and cybersecurity practitioners interested in AI-driven security and modern network will also find this book useful as a reference.

Inhalt

.- Foundations - Computer Networks and Artificial Intelligence.
.- Cyber Threat Landscape and AI-Driven Defenses.
.- Containerization and Network Security with Docker.
.- Configuration Automation Using Ansible for Servers and Cisco Devices.
.- Infrastructure as Code with Terraform.
.- DevSecOps PipelineCombining Docker, Ansible, Terraform, and AI.
.- Ethical Hacking and Penetration Testing.
.- Incident Response and Threat Hunting with AI.
.- Advanced TopicsOrchestration, IoT, and Cisco at Scale.
.- Capstone Projects, Case Studies, and the Road Ahead.