Transforming Cybersecurity with Machine Learning [Hardcover]

This book provides an in-depth exploration of the dynamic intersection between machine learning (ML) and cybersecurity, offering a detailed analysis of how these technologies are reshaping the security landscape

This book provides an in-depth exploration of the dynamic intersection between machine learning (ML) and cybersecurity, offering a detailed analysis of how these technologies are reshaping the security landscape. It tracks the signi
cant progress of machine learning in the context of cybersecurity, providing insights into the latest advancements, emerging trends, and the challenges ahead. Crafted with a discerning audience in mind, this book is a valuable resource for academic researchers, industry practitioners, and students alike. It is particularly suitable for those interested in understanding the transformative role ML plays in modern cybersecurity.

1. An overview of the machine learning role in cybersecurity transformation. 2. Machine learning (ML). 3. Understanding data, datasets, and training for ML. 4. Building training and testing datasets. 5. Data analytics. 6. Deep learning and neural networks. 7. Modern cybersecurity tools. 8. Machine learning in cybersecurity. 9. ML-powered top platforms.

Kutub Thakur, PhD, is a distinguished cybersecurity expert, educator, and researcher with extensive experience across both public and private sectors, including the United Nations, major
nancial institutions, utility companies, and academic institutions. He earned a PhD in computer science with a specialization in cybersecurity at Pace University in New York, an MS in electrical and computer control systems engineering at the University of Wisconsin, and a BS in computer systems technology at the City University of New York.

Al-Sakib Khan Pathan, PhD, is a professor in the Computer Science and Engineering Departmel“A