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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.
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