THE AUTONOMOUS SOC
How Artificial Intelligence Is Reinventing Cyber DefenseBy Silver Nsaka
Length3h 51m
About this audiobook
In an era where cyberattacks launch in milliseconds and breach organizations in seconds, the traditional Security Operations Center is reaching the end of its operational viability. THE AUTONOMOUS SOC is the definitive guide to the AI-driven transformation that every security organization must undertake to survive the next decade of cyber warfare. Written by Silver Nsaka — cybersecurity strategist, AI architect, and founder of Kingdom AI Solutions — this book delivers a complete blueprint from the failing SOC of today to the autonomous, AI-driven cyber defense platform of tomorrow. WHAT YOU WILL LEARN: How machine learning, behavioral analytics, and graph-based detection replace static rules with systems that think and adapt. How LLMs and agentic AI systems transform analysts into strategic orchestrators of autonomous defense. How to architect a complete AI-SOC platform on AWS, Azure, and Google Cloud.
Audiobook details
GenreTechnology
Length3 hrs 51 mins
Narrated byListen with 1,000+ voices
FormateBook with Audio
Publish dateMar 27, 2026
LanguageEnglish
Table of contents
1Introduction
2Foreword
3Preface
4Table of Contents
5Chapter 1: The Broken SOC — Why Traditional Security Operations Are Failing
Show all chaptersShow less
6The Alert Tsunami
7Mean Time to Detect and Mean Time to Respond: The Metrics of Failure
8The Tool Proliferation Problem
9The Talent Crisis
10Architecture Diagrams: The Traditional SOC vs. The AI-SOC
11The Case for Radical Transformation
12Traditional SOC vs. AI-SOC: Key Metrics
13Chapter 2: The Threat Landscape Has Evolved — Your Defenses Have Not
14The New Anatomy of Attack
15AI-Enhanced Attack Techniques
16The Speed Problem: Why Rules Cannot Keep Up
17Supply Chain and Third-Party Risk: The Expanding Attack Surface
18Cloud-Native Attack Surfaces
19Chapter 3: The Human Bottleneck — Alert Fatigue, Analyst Burnout, and the Talent Crisis
20The Neuroscience of Alert Fatigue
21The Staffing Model Impossibility
22Designing for Human-AI Collaboration
23Chapter 4: The Economics of Cyber Failure — The ROI of Legacy Security Is Collapsing
24The True Cost of a Security Breach
25The ROI Framework for AI-SOC Investment
26Chapter 5: The Case for Transformation — What a Modern AI-SOC Must Deliver
27Defining the AI-SOC: Capabilities and Characteristics
28The AI-SOC Maturity Model
29AI-SOC Maturity Model
30Chapter 6: Machine Learning for Threat Detection — From Rules to Intelligence
31A Taxonomy of Machine Learning in Security
32Feature Engineering for Security ML
33Behavioral Analytics: Building Baselines That Matter
34ML Model Deployment and MLOps for Security
35Chapter 7: Behavioral Analytics and UEBA — The New Perimeter
36User and Entity Behavior Analytics: Architecture and Implementation
37Insider Threat Detection: The Most Difficult Problem
38Chapter 8: Graph-Based Threat Detection and Attack Path Analysis
39Why Graphs Are Natural Security Models
40Attack Graph Analysis and MITRE ATT&CK Mapping
41Chapter 9: Large Language Models in the SOC — The AI Security Analyst
42LLMs Transform SOC Operations
43Building a Security-Specific LLM: Fine-Tuning and RAG
44LLM Security Copilots: Architecture and Implementation
45Chapter 10: AI Threat Hunting — Autonomous Discovery of Hidden Threats: The Evolution of Threat Hunting
46Chapter 11: AI Anomaly Detection — Finding What Rules Cannot See
47Taxonomy of Anomaly Detection Techniques
48ML Techniques for Security: Selection Guide
49Chapter 12: The AI-SOC Reference Architecture
50The Complete AI-SOC Architecture
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