This book shows how machine learning (ML) methods can be used to enhance cyber security operations, including detection, modeling, monitoring as well as defense against threats to sensitive data and security systems. Filling an important gap between ML and cyber security communities, it discusses topics covering a wide range of modern and practical ML techniques, frameworks and tools.

In comparison to Industry 4.0, Industry 5.0 is seen as the next industrial revolution, with the goal of leveraging the creativity of human experts in combination with efficient, intelligent, and accurate machines to provide resource-efficient and user-preferred solutions. With the improvements in social networks, cloud, and the internet of things (IoT)-based technologies, the requirement for a strong cyber security system, particularly in the healthcare sector, is increasing. Cyber Trafficking, Threat Behavior, and Malicious Activity Monitoring for Healthcare Organizations provides a comprehensive review of techniques and applications of Industry 5.0-enabled intelligent healthcare-centric cyber security. The goal of this book is to close the gap between AI and cyber security. Covering topics such as malicious activity, the dark web, and smart healthcare systems, this premier reference source is an essential resource for healthcare administrators, IT managers, system developers, system architects, IT specialists, students and educators of higher education, librarians, researchers, and academicians.