The fast-growing number of patients suffering from various ailments has overstretched the carrying capacity of traditional healthcare systems. This handbook addresses the increased need to tackle security issues and preserve patients’ privacy concerns in AIoMT devices and systems. Handbook of Security and Privacy of AI-Enabled Healthcare Systems and the Internet of Medical Things provides new insights into the deployment, application, management, and benefi ts of AIoMT by examining real-world scenarios. The handbook takes a critical look at existing security designs and offers solutions to revamp traditional security architecture, including the new design of effi cient intrusion detection algorithms, attack prevention techniques, and both cryptographic and noncryptographic solutions. The handbook goes on to discuss the critical security and privacy issues that affect all parties in the healthcare ecosystem and provides practical AI-based solutions. This handbook offers new and valuable information that will be highly beneficial to educators, researchers, and others. .

This book explores the concepts and techniques of IoT, AI, and blockchain. Also discussed is the possibility of applying blockchain for providing security in various domains. The specific highlight of this book is focused on the application of integrated technologies in enhancing data models, better insights and discovery, intelligent predictions, smarter finance, smart retail, global verification, transparent governance, and innovative audit systems. The book allows both practitioners and researchers to share their opinions and recent research in the convergence of these technologies among academicians and industry people. The contributors present their technical evaluation and compare it with existing technologies. Theoretical explanation and experimental case studies related to real-time scenarios are also included. This book pertains to IT professionals, researchers and academicians working on fourth revolution technologies.

This book explores the concepts and techniques of IoT, AI, and blockchain. Also discussed is the possibility of applying blockchain for providing security in various domains. The specific highlight of this book is focused on the application of integrated technologies in enhancing data models, better insights and discovery, intelligent predictions, smarter finance, smart retail, global verification, transparent governance, and innovative audit systems. The book allows both practitioners and researchers to share their opinions and recent research in the convergence of these technologies among academicians and industry people. The contributors present their technical evaluation and compare it with existing technologies. Theoretical explanation and experimental case studies related to real-time scenarios are also included. This book pertains to IT professionals, researchers and academicians working on fourth revolution technologies.

Medical decision support systems (MDSS) are computer-based programs that analyse data within a patient's healthcare records to provide questions, prompts, or reminders to assist clinicians at the point of care. Inputting a patient's data, symptoms, or current treatment regimens into an MDSS, clinicians are assisted with the identification or elimination of the most likely potential medical causes, which can enable faster discovery of a set of appropriate diagnoses or treatment plans. Explainable AI (XAI) is a "white box" model of artificial intelligence in which the results of the solution can be understood by the users, who can see an estimate of the weighted importance of each feature on the model's predictions, and understand how the different features interact to arrive at a specific decision. This book discusses XAI-based analytics for patient-specific MDSS as well as related security and privacy issues associated with processing patient data. It provides insights into real-world scenarios of the deployment, application, management, and associated benefits of XAI in MDSS. The book outlines the frameworks for MDSS and explores the applicability, prospects, and legal implications of XAI for MDSS. Applications of XAI in MDSS such as XAI for robot-assisted surgeries, medical image segmentation, cancer diagnostics, and diabetes mellitus and heart disease prediction are explored.

Fifth generation (5G) wireless networks are now commercialized, and the research focus has shifted towards sixth generation (6G) wireless systems. The integration of sensor nodes and massive machine type communication (MTC) devices (MDs) in ubiquitous 5G networks has facilitated the design of critical enabling technologies to support billions of data-hungry applications. By leveraging sensor nodes in wireless sensor networks (WSNs), sensitive user information can be harvested and transmitted to receivers via WSN-assisted channels, which are often not well secured. Consequently, sensitive user information can be intercepted and used unlawfully. The security and confidentiality measures used for data transmission over existing 5G WSN-assisted channels are limited. 6G systems are envisaged to face fiercer security challenges. In 6G wireless networks, a new set of sensing and precise localization techniques are predicted. Thus, the need to secure user information against adversarial attacks needs to be implemented at the design stage. The book proposes viable solutions to revamp traditional security architecture by addressing critical security challenges in commercialized 5G and envisioned 6G wireless communication systems. Expert contributors bring new insights into real-world scenarios for the deployment, applications and management of robust, secure, and efficient security schemes for massive devices in 6G wireless networks. Finally, the book discusses critical security and privacy issues affecting the wireless ecosystem and provides practical AI-based solutions. Security and Privacy Schemes for Dense 6G Wireless Communication Networks is an essential reference for industry and academic researchers; scientists, engineers, lecturers and advanced students in the fields of cybersecurity wireless communication and networking, network security, computing, data science, AI/ML/DL, and sensing, as well as cybersecurity professionals and 6G standardization experts.