6The Alert Tsunami
53The Security Data Lake Architecture
7Mean Time to Detect and Mean Time to Respond: The Metrics of Failure
54Telemetry at Scale: Engineering for Billions of Events
8The Tool Proliferation Problem
55Chapter 14: The AI-Powered SIEM — From Log Aggregation to Intelligent Detection: Reinventing the SIEM for AI-First Operations
9The Talent Crisis
56Chapter 15: SOAR 2.0 — AI-Orchestrated Security Automation
10Architecture Diagrams: The Traditional SOC vs. The AI-SOC
57The Evolution of Security Orchestration
11The Case for Radical Transformation
58Automated Incident Triage at Scale
12Traditional SOC vs. AI-SOC: Key Metrics
59Chapter 16: Detection Engineering with AI: AI-Generated Detection Rules
13Chapter 2: The Threat Landscape Has Evolved — Your Defenses Have Not
60Chapter 17: AI-Driven Threat Intelligence: Transforming Threat Intelligence with AI
14The New Anatomy of Attack
61Chapter 18: Cloud-Native AI-SOC on AWS, Azure, and GCP
15AI-Enhanced Attack Techniques
62AWS AI-SOC Reference Architecture
16The Speed Problem: Why Rules Cannot Keep Up
63Azure AI-SOC Reference Architecture
17Supply Chain and Third-Party Risk: The Expanding Attack Surface
64Google Cloud AI-SOC Reference Architecture
18Cloud-Native Attack Surfaces
65AI-SOC Technology Stack: Component Selection Guide
19Chapter 3: The Human Bottleneck — Alert Fatigue, Analyst Burnout, and the Talent Crisis
66Chapter 19: Introduction to Agentic AI Security Systems
20The Neuroscience of Alert Fatigue
67What Makes an AI System Agentic?
21The Staffing Model Impossibility
68LangChain and Agent Frameworks for Security
22Designing for Human-AI Collaboration
69Chapter 20: Detection Agents — Autonomous Threat Discovery: Building Production Detection Agents
23Chapter 4: The Economics of Cyber Failure — The ROI of Legacy Security Is Collapsing
70Chapter 21: Incident Response Agents — Automated Investigation and Containment: The Incident Response Agent Architecture
24The True Cost of a Security Breach
71Chapter 22: Threat Hunting Agents — Proactive Defense at Scale: Autonomous Threat Hunting at Enterprise Scale
25The ROI Framework for AI-SOC Investment
72Chapter 23: Multi-Agent SOC Systems — Coordination and Orchestration: The Multi-Agent Security Architecture
26Chapter 5: The Case for Transformation — What a Modern AI-SOC Must Deliver
73Chapter 24: Security Copilots — AI-Augmented Human Analysts
27Defining the AI-SOC: Capabilities and Characteristics
74The AI Security Analyst Experience
28The AI-SOC Maturity Model
75AI Security Agent Capabilities Matrix
29AI-SOC Maturity Model
76Chapter 25: The Autonomous SOC Platform — Integration and Operations: Platform Architecture Integration
30Chapter 6: Machine Learning for Threat Detection — From Rules to Intelligence
77Chapter 26: Self-Healing Security Infrastructure: Autonomous Defense and Remediation
31A Taxonomy of Machine Learning in Security
78Chapter 27: AI Red Team vs. AI Blue Team — Adversarial Machine Learning: The Adversarial AI Challenge
32Feature Engineering for Security ML
79Chapter 28: Next-Generation AI Fraud Detection — Real-Time Defense at Transaction Scale
33Behavioral Analytics: Building Baselines That Matter
80The Architecture of AI-Powered Fraud Detection
34ML Model Deployment and MLOps for Security
81Smart Contract Audit Trails and Blockchain for Fraud Evidence
35Chapter 7: Behavioral Analytics and UEBA — The New Perimeter
82Chapter 29: AI-Powered SOC Metrics — Measuring What Matters: The AI-SOC Measurement Framework
36User and Entity Behavior Analytics: Architecture and Implementation
83Chapter 30: SOC Transformation Roadmap — From Legacy to Autonomous
37Insider Threat Detection: The Most Difficult Problem
84The 36-Month Transformation Journey
38Chapter 8: Graph-Based Threat Detection and Attack Path Analysis
85SOC KPI Dashboard: Target Metrics by Maturity Level
39Why Graphs Are Natural Security Models
86Chapter 31: Nation-State AI Cyber Operations: AI in State-Sponsored Cyber Programs
40Attack Graph Analysis and MITRE ATT&CK Mapping
87Chapter 32: AI vs. AI — The Coming Cyber Arms Race: The Automated Offense-Defense Equilibrium
41Chapter 9: Large Language Models in the SOC — The AI Security Analyst
88Chapter 33: Self-Defending Networks and Zero Trust AI: The Architecture of Self-Defending Infrastructure
42LLMs Transform SOC Operations
89Chapter 34: The AI Security Ecosystem — Standards, Governance, and Ethics: Responsible AI in Security Operations
43Building a Security-Specific LLM: Fine-Tuning and RAG
90Chapter 35: The Horizon — Autonomous Cyber Defense in 2030 and Beyond: The Security Future We Are Building
44LLM Security Copilots: Architecture and Implementation
91Appendix A: MITRE ATT&CK Framework and AI Integration
45Chapter 10: AI Threat Hunting — Autonomous Discovery of Hidden Threats: The Evolution of Threat Hunting
92Appendix B: AI-SOC Technology Stack Reference
46Chapter 11: AI Anomaly Detection — Finding What Rules Cannot See
93Appendix C: Implementation Checklist
47Taxonomy of Anomaly Detection Techniques
94Appendix D: Glossary of AI Security Terms
