Artificial Intelligence and Machine Learning in Cybersecurity

A Comprehensive Guide to Improving Cybersecurity Protocol

Richard Gwashy Young, PhD

• Publisher: Productivity Press
• Year: 2025
• eBook ISBN: 9781040383766
• Topic: Business
• Subtopic: Information Management
• Index: Business

Artificial Intelligence and Machine Learning in Cybersecurity: A Comprehensive Guide to Improving Cybersecurity Protocol is a comprehensive exploration of the intersection between cutting-edge technology and cybersecurity practices. This book offers readers an in-depth understanding of how artificial intelligence (AI) and machine learning (ML) are reshaping the cybersecurity landscape. It begins with foundational concepts, explaining AI and ML's principles and their transformative potential within various sectors, particularly cybersecurity. This book uniquely combines theoretical insights and practical applications, making it an essential resource for graduate students and cybersecurity professionals eager to expand their knowledge and skills.

The book's uniqueness lies in its detailed analysis of how AI and ML can predict and counteract emerging threats in real time, shifting the paradigm from reactive to proactive cybersecurity measures. By delving into a wide range of topics, such as AI-powered Intrusion Detection and Prevention Systems (IDPS) and endpoint security, the author provides case studies and examples from sectors like finance and healthcare. This hands-on approach not only illustrates successful implementations but also highlights potential challenges, offering balanced perspectives and strategies to overcome hurdles. The inclusion of ethical considerations around AI usage in cybersecurity further distinguishes it as a forward-thinking guide.

As cyber threats continue to evolve, the need for advanced AI and ML methodologies becomes increasingly critical. This book addresses this urgency by equipping readers with contemporary knowledge and tools necessary to leverage these technologies effectively. The discussion of future trends, such as AI-powered quantum security and necessary policy implications, ensures that readers are well-prepared to navigate the complexities of cybersecurity in the coming decades. Ultimately, it serves as both an educational textbook for students and a practical guide for cyber practitioners, offering a roadmap for implementing AI-driven cybersecurity solutions that enhance threat detection, response, and prevention.

Table of contents

• Cover
• Half-Title
• Title
• Copyright
• Dedication
• Contents
• Preface
• Acknowledgments
• About the Author
• Introduction
• 1 Introduction to AI, ML, and Cybersecurity
• 2 The Cyber Threat Landscape in the 21st Century
• 3 Foundations of Artificial Intelligence and Machine Learning in Cybersecurity
• 4 Predictive Analytics and Threat Intelligence with AI and ML
• 5 Automating Security Protocols Using AI and ML
• 6 AI-Powered Intrusion Detection and Prevention Systems (IDPS)
• 7 AI and ML in Endpoint Security and Zero Trust Models
• 8 Enhancing Network Security with AI and ML
• 9 AI and ML in Combating Cybercrime and Fraud
• 10 AI and ML in Cybersecurity Operations and Security Operations Centers (SOCs)
• 11 Ethical Considerations and Risks of AI/ML in Cybersecurity
• 12 Conclusion: Leveraging Artificial Intelligence and Machine Learning to Improve Cybersecurity Protocols
• Appendices
• References
• Index