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Artificial Intelligence for Security

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"Artificial Intelligence (AI) for security management explores terminologies of security and how AI can be applied to automate security processes. Additionally, the text provides detailed explanations and recommendations for how implement procedures. Practical examples and real-time use cases are evaluated and suggest appropriate algorithms based on the author’s experiences. Threat and associated securities from the data, process, people, things (e.g., Internet of things), systems, and actions were used to develop security knowledge base, which will help readers to build their own knowledge base. This book will help the readers to start their AI journey on security and how data can be applied to drive business actions to build secure environment."

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,ontents

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.

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Uploaded on
August 2, 2024
Number of pages
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Written in
2021/2022
Type
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