Acknowledgments
Chapter 1Introduction
Chapter 2Introduction to Security
Chapter 3How AI and Security Come Together?
Chapter 4Knowledgebase
Chapter 5AI Solutions for Security
Chapter 6Industry Domain
Chapter 7Conclusion
CHAPTER 1
Introduction
Target Audience
What Do You Get from the Book?
What This Book Covers
This Book’s Mind Map
Organization of Chapters
Introduction to Security
Introduction to the AI Knowledge Base
How AI Security Comes Together
Business Use Cases
AI Solutions for Security
Industry Domain
Conclusion
References
Chapter Outline
Book introduction
Organization of the book
Chapter introduction
Key Learning Points
, Learn and understand the introduction
Target Audience
This book mainly focuses on how artificial intelligence (AI) can be applied to security
management. This book follows current trends of AI in the branches of natural language processing,
natural language question and answering systems, conversational AI (Reddy 2018) in security
domains, AI supporting drones, AI cybersecurity, Internet of things (IoT) devices, and use cases.
Applicable AI topics target the following groups:
Corporate top executives, founders, chief technology officers, chief information
officers, chief data officers, chief security officers, data scientists, data architects, AI
designers, AI engineers, project managers, and consultants to understand how to manage
security using AI.
Students, teachers, and developers will find this book useful and practical. It will
provide an overview of many AI components and introduce how AI can be used in
corporate environments and start-up companies.
Anybody who strives to understand how AI can be used for security.
What Do You Get from the Book?
Understand and learn about AI and how to apply AI to security.
Design and apply knowledge-based AI solutions to solve security problems.
The design of AI applied systems relies primarily on the following:
Subject Matter Experts. This means having a practical view of how
solutions can be used. In this book, security is used as an example with case studies.
Appropriately applied mathematics and algorithms are used in the book. Do
not skip the mathematical equations if you have the need to study them. It is
important to note that AI relies heavily on mathematics.
Applied physics and usage in hardware systems and futuristic approaches
from quantum computers to parallel processing of the quantum computer handling
network. AI is evolving into a new era of possible opportunities. New concepts and
applied creative ideas are introduced in the futuristic AI chapter.
Decision theory, decision-making processes, the Markov decision process, and
algorithms.
What This Book Covers
This book introduces AI and explains how AI is applied to corporations, start-ups, and companies
of all sizes to help automate the tedious job of maintaining security. AI and machine learning can
automate the working environment of an organization, thus creating resources for
organizational employees. The following questions are addressed in this book.
How do I get true value from AI?
What is the business use cases for AI with visionary?
, How do I identify the best business case for AI adoption and evaluate opportunities?
Should I build or buy an AI platform?
How do I find and recruit top AI talent for my enterprise?
How will I bring AI into my business to increase revenue or decrease costs?
How can I facilitate AI adoption within my organization?
This book addresses how to manage data collection, data preparation, data transformation, data
security, and how to use the data to align AI use case.
Figure 1.1 Mind map of the book
A mind map for the book’s introduction is provided in Figure 1.1. This figure summarizes what is
discussed in the book and the organization of chapters.