Foundations, Frameworks, and Field Practice
Buch, Englisch, 280 Seiten, Format (B × H): 178 mm x 254 mm
ISBN: 979-8-8688-3236-9
Verlag: APRESS L.P.
Agentic AI is no longer theoretical—but most cybersecurity teams are still struggling to move from concept to production. fills the critical gap between vendor hype and academic abstraction, delivering a practical, engineering-first guide that security architects can apply immediately. This is the book for professionals who need to build real systems—not just talk about them.
At its core, this book argues that agentic AI is not a toolset but a new operating model for the Security Operations Center. That shift changes everything: architecture, governance, and risk. Unlike other titles, it refuses to separate capability from security. Offensive and defensive use cases are treated together, reflecting the real dual-use nature of agentic systems and equipping readers to design—and defend—against both.
Timeliness is what makes this book essential. It is the first practitioner-focused guide to unify three converging forces shaping modern security: MCP-based agentic systems, their emerging and largely undocumented attack surface, and the parallel migration to post-quantum cryptography. Each is complex on its own—together, they define the next generation of security architecture. This book addresses them as a single, integrated challenge.
Built for real-world use, every chapter follows a ‘what / how / why’ structure and culminates in runnable, production-grade architectures. Readers don’t just learn concepts—they deploy them, using reference implementations drawn from actual environments and supported by a living GitHub repository. From MCP servers and adversary emulation to AI-driven detection and quantum-resistant infrastructure, this is hands-on guidance grounded in reality.
For practitioners who need clarity, credibility, and actionable design patterns, stands apart. It is unapologetically practical, rigorously honest about risks, and singular in its integration of architecture, security, and emerging AI paradigms—making it a must-have resource for building the next generation of secure systems.
What You Will Learn:
- Master the conceptual architecture of agentic AI
- Build, harden, and govern production-grade Model Context Protocol (MCP) servers for network and security operations
- Operationalize AI-driven offensive security through Kali Linux integration via MCP and MITRE Caldera as an LLM-driven adversary emulation platform
- Defend against the agentic AI attack surface
- Plan and execute the post-quantum cryptographic migration in AI-era infrastructure
- Apply machine learning and deep learning to autonomous malware detection and threat classification
Who this Book is for:
The target reader is a working network or security practitioner — a SOC analyst, network engineer, security architect, security engineer, or incident responder — who is being asked, by their employer or by the field, to integrate agentic AI into their operational practice and who needs guidance that is more concrete than vendor whitepapers and more applicable than academic papers.
The book does not assume prior experience with agentic AI specifically, but it does assume the reader is comfortable with at least one of the three domains the book unifies: enterprise network operations, security operations, or applied machine learning. Readers from adjacent communities — DevSecOps engineers, cloud security architects, AI/ML platform engineers responsible for AI safety — will also find Part II directly applicable to their work.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Part I: Foundations.- Chapter 1: The Cybersecurity Imperative: Foundations, Threats, and the Digital Battlefield.- Chapter 2: Artificial Intelligence in Cybersecurity: A New Paradigm for Intelligent Defense.- Chapter 3: From Reactive to Autonomous: Foundations and Architecture of Agentic AI.- Chapter 4: Building and Operating Agentic AI: Deployment, Multi-Agent Systems, and Autonomous Defense.- Chapter 5: Agentic AI as Weapon and Governed Tool: Offensive Capabilities, Agent Security, and the Governance Imperative.- Part II: Implementation and Operations.- Chapter 6: AI-Augmented Network Management: The Model Context Protocol as a Universal Integration Layer.- Chapter 7: From Consumer to Creator: Extending and Building MCP Servers for Cybersecurity and Network Operations.- Chapter 8: Kali Linux Meets AI: From ATT&CK-Aligned Tooling to Model Context Protocol and Natural Language Penetration Testing.- Chapter 9: Autonomous Red Teaming: AI-Augmented Adversary Emulation with MITRE Caldera and the Model Context Protocol.-
Chapter 10: AI-Powered Malware Detection: Machine Learning, Deep Learning, and Agentic Intelligence in Autonomous Threat Classification.- Chapter 11: Post-Quantum Cryptography and Artificial Intelligence: Securing the Foundations of Autonomous Defense.
