Dilli Prasad Sharma – författare

Digital technology is increasingly used in the healthcare sector, and healthcare organizations handle sensitive and confidential information that needs to be kept secure and protected. Therefore, the importance of cybersecurity in healthcare cannot be overstated. Cyber threats can compromise patient data, disrupt healthcare services, and put personal safety at risk. This book provides an understanding of cybersecurity in healthcare, which is crucial for protecting personal information, ensuring compliance with regulations, maintaining patient trust, and preventing cyber-attacks. Before defining cybersecurity in healthcare, the authors introduce the healthcare environment and cybersecurity basics to readers. They then emphasize the importance of data protection and privacy, software, and personal cybersecurity. Also, they highlight the importance of educating staff about cybersecurity. The discussion continues with data and information security in healthcare, including data threats and vulnerabilities, the difference between data protection and privacy, and how to protect data. Afterward, they focus on the software system frameworks and types of infra-security and app security in healthcare. A key goal of this book is to provide readers with an understanding of how to detect and prevent cyber-attacks in the healthcare sector and how to respond to and recover from them. Moreover, it gives them an insight into cybersecurity vulnerabilities in healthcare and how they are mitigated. A chapter on cybersecurity ethics and healthcare data governance frameworks is also included in the book. The last chapter explores the challenges healthcare organizations face in maintaining security compliance and security practice guidelines that exist. By understanding the risks and challenges of cybersecurity in healthcare, healthcare providers and organizations can better protect sensitive and confidential data and ensure the safety and privacy of those they serve.

This book presents an overview of the emerging topics in Artificial Intelligence (AI) and cybersecurity and addresses the latest AI models that could be potentially applied to a range of cybersecurity areas. Furthermore, it provides different techniques of how to make the AI algorithms secure from adversarial attacks. The book presents the cyber threat landscape and explains the various spectrums of AI and the applications and limitations of AI in cybersecurity. Moreover, it explores the applications and limitations of secure AI. The authors discuss the three categories of machine learning (ML) models and reviews cutting-edge recent Deep Learning (DL) models. Furthermore, the book provides a general AI framework in security as well as different modules of the framework; similarly, chapter four proposes a general framework for secure AI. It explains different aspects of network security including malware and attacks.

The book also includes a comprehensive study of various scopes of application security; categorised into three groups of smartphone, web application, and desktop application and delves into the concepts of cloud security. The authors discuss state-of-the-art Internet of Things (IoT) security and describe various challenges of AI for cybersecurity, such as data diversity, model customising, explainability, and time complexity and includes some future work. They provide a comprehensive understanding of adversarial machine learning including the up-to-date adversarial attacks and defences. The book finishes off with a discussion of the challenges and future work in secure AI.