Agbotiname Lucky Imoize – författare

Federated Learning for Digital Healthcare Systems critically examines the key factors that contribute to the problem of applying machine learning in healthcare systems and investigates how federated learning can be employed to address the problem. The book discusses, examines, and compares the applications of federated learning solutions in emerging digital healthcare systems, providing a critical look in terms of the required resources, computational complexity, and system performance.In the first section, chapters examine how to address critical security and privacy concerns and how to revamp existing machine learning models. In subsequent chapters, the book's authors review recent advances to tackle emerging efficient and lightweight algorithms and protocols to reduce computational overheads and communication costs in wireless healthcare systems. Consideration is also given to government and economic regulations as well as legal considerations when federated learning is applied to digital healthcare systems.

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 Artificial Intelligence of Medical Things (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 benefits 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.

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 Artificial Intelligence of Medical Things (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 benefits 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.

The text provides a comprehensive study of the application of advanced artificial intelligence (AI) in next-generation wireless communications with a focus on theory, standardization, and core development. It further highlights AI-enabled intelligent architecture for sixth-generation (6G) networks to realize smart resource management, automatic network adjustment, and intelligent service layers. The book covers artificially assisted non-orthogonal multiple access schemes for 6G communication.

This book:

It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, and computer engineering.

The text provides a comprehensive study of the application of advanced artificial intelligence (AI) in next-generation wireless communications with a focus on theory, standardization, and core development. It further highlights AI-enabled intelligent architecture for sixth-generation (6G) networks to realize smart resource management, automatic network adjustment, and intelligent service layers. The book covers artificially assisted non-orthogonal multiple access schemes for 6G communication.

This book:

It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, and computer engineering.

This book studies the evolution of sustainable green smart cities and demonstrates solutions for green environmental issues using modern industrial IoT solutions. It is a ready reference with guidelines and a conceptual framework for context-aware product development and research in the IoT paradigm and Big Data Analytics for a Green Environment. It brings together the most recent advances in IoT and Big Data in Green Environments, emerging aspects of the IoT and Big Data for Green Cities, explores key technologies, and develops new applications in this research field.

Key Features:

• Discusses the framework for development and research in the IoT Paradigm and Big Data Analytics.

• Highlights threats to the IoT architecture and Big Data Analytics for a Green Environment.

• Present the I-IoT architecture, I-IoT applications, and their characteristics for a Green Environment.

• Provides a systematic overview of the state-of-the-art research efforts.

• Introduces necessary components and knowledge to become a vital part of the IoT revolution for a Green Environment.

This book is for professionals and researchers interested in the emerging technology of sustainable development, green cities, and Green Environment.

This book studies the evolution of sustainable green smart cities and demonstrates solutions for green environmental issues using modern industrial IoT solutions. It is a ready reference with guidelines and a conceptual framework for context-aware product development and research in the IoT paradigm and Big Data Analytics for a Green Environment. It brings together the most recent advances in IoT and Big Data in Green Environments, emerging aspects of the IoT and Big Data for Green Cities, explores key technologies, and develops new applications in this research field.

Key Features:

• Discusses the framework for development and research in the IoT Paradigm and Big Data Analytics.

• Highlights threats to the IoT architecture and Big Data Analytics for a Green Environment.

• Present the I-IoT architecture, I-IoT applications, and their characteristics for a Green Environment.

• Provides a systematic overview of the state-of-the-art research efforts.

• Introduces necessary components and knowledge to become a vital part of the IoT revolution for a Green Environment.

This book is for professionals and researchers interested in the emerging technology of sustainable development, green cities, and Green Environment.

This book offers a comprehensive exploration of cutting-edge research and developments in the field of cybersecurity. It presents a curated collection of chapters that reflect the latest in empirical data approximation, malware recognition, information security technologies, and beyond.

Advancements in Cybersecurity: Next-Generation Systems and Applications offers readers a broad perspective on the multifaceted challenges and solutions in contemporary cybersecurity through topics ranging from the application of blockchain technology in securing information systems, to the development of new cost functions for the iterative generation of cryptographic components. The book not only addresses technical aspects but also provides insights into the theoretical frameworks and practical applications that underpin the development of robust cybersecurity systems. It explores the optimization of algorithms for generating nonlinear substitutions, the application of machine learning models for security evaluation, and the implementation of deep learning techniques for detecting sophisticated cyber-attacks. Through its in-depth analysis and forward-looking perspectives, this book contributes significantly to advancing cybersecurity research and practice, paving the way for a safer digital future.

This book is designed to serve as an essential resource for researchers, practitioners, policymakers, and engineers in the fields of ICT, next-generation computing and IT security, including cryptography, AI/ML/DL, cyber resilience, network security, threat modeling and risk assessment, digital forensics, secure software development, hardware security, and human-centric security.

This book offers a comprehensive exploration of cutting-edge research and developments in the field of cybersecurity. It presents a curated collection of chapters that reflect the latest in empirical data approximation, malware recognition, information security technologies, and beyond.

Advancements in Cybersecurity: Next-Generation Systems and Applications offers readers a broad perspective on the multifaceted challenges and solutions in contemporary cybersecurity through topics ranging from the application of blockchain technology in securing information systems, to the development of new cost functions for the iterative generation of cryptographic components. The book not only addresses technical aspects but also provides insights into the theoretical frameworks and practical applications that underpin the development of robust cybersecurity systems. It explores the optimization of algorithms for generating nonlinear substitutions, the application of machine learning models for security evaluation, and the implementation of deep learning techniques for detecting sophisticated cyber-attacks. Through its in-depth analysis and forward-looking perspectives, this book contributes significantly to advancing cybersecurity research and practice, paving the way for a safer digital future.

This book is designed to serve as an essential resource for researchers, practitioners, policymakers, and engineers in the fields of ICT, next-generation computing and IT security, including cryptography, AI/ML/DL, cyber resilience, network security, threat modeling and risk assessment, digital forensics, secure software development, hardware security, and human-centric security.