Blockchain Technology Solutions for the Security of IoT-Based Healthcare Systems explores the various benefits and challenges associated with the integration of blockchain with IoT healthcare systems, focusing on designing cognitive-embedded data technologies to aid better decision-making, processing and analysis of large amounts of data collected through IoT. This book series targets the adaptation of decision-making approaches under cognitive computing paradigms to demonstrate how the proposed procedures, as well as big data and Internet of Things (IoT) problems can be handled in practice. Current Internet of Things (IoT) based healthcare systems are incapable of sharing data between platforms in an efficient manner and holding them securely at the logical and physical level. To this end, blockchain technology guarantees a fully autonomous and secure ecosystem by exploiting the combined advantages of smart contracts and global consensus. However, incorporating blockchain technology in IoT healthcare systems is not easy. Centralized networks in their current capacity will be incapable to meet the data storage demands of the incoming surge of IoT based healthcare wearables. - Highlights the coming surge of IoT based healthcare wearables and predicts that centralized networks in their current capacity will be incapable to meet the data storage demands - Outlines the major benefits and challenges associated with the integration of blockchain with IoT healthcare systems - Investigates use-cases and the latest research on securing healthcare IoT systems using blockchain technology - Discusses the evolution of blockchain technology, from fundamental theories to applications in healthcare systems - Gathers and investigates the most recent research solutions that handle security and privacy threats while considering resource constrained IoT healthcare devices

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. .

This book sheds light on the cyber security challenges associated with nextgeneration computing technologies, emphasizing the serious threats posed to individuals, businesses, and nations. With everything becoming increasingly interconnected via the Internet, data security becomes paramount. As technology advances, people need to secure their data communication processes. Personal data security, including data integrity and confidentiality, is particularly vulnerable. Therefore, the concept of cyber security forensics emerges to ensure data security for everyone, addressing issues such as data control, hijacking, and threats to personal devices such as mobile phones, laptops, and other smart technologies. This book covers key topics related to cyber security in next-generation computing technologies, ultimately enhancing the quality of life for citizens, facilitating interaction with smart governments, and promoting secure communication processes. KEY FEATURES Highlights innovative principles and practices using next generation computing technologies based cybersecurity Presents an introduction to recent trends regarding the convergence of AI/ML in cybersecurity Offers an overview of theoretical, practical, simulation concepts of cybersecurity

The emergence of the Internet of Medical Things (IoMT) is transforming the management of diseases, improving diseases diagnosis and treatment methods, and reducing healthcare costs and errors. This book covers all the essential aspects of IoMT in one place, providing readers with a comprehensive grasp of IoMT and related technologies. Data Modelling and Analytics for the Internet of Medical Things integrates the architectural, conceptual, and technological aspects of IoMT, discussing in detail the IoMT, connected smart medical devices, and their applications to improve health outcomes. It explores various methodologies and solutions for medical data analytics in healthcare systems using machine learning and deep learning approaches, as well as exploring how technologies such as blockchain and cloud computing can further enhance data analytics in the e-health domain. Prevalent IoMT case studies and applications are also discussed. This book is suitable for scientists, design engineers, system integrators, and researchers in the field of IoMT. It will also be of interest to postgraduate students in computer science focusing on healthcare applications and a supplementary reading for IoMT courses.

In an era defined by rapid technological advancements and an increasingly interconnected world, the challenges and opportunities presented by digitalization demand a new approach. The digital world, characterized by optimized, sustainable, and digitally networked solutions, necessitates the integration of intelligence systems, machine learning, deep learning, blockchain methods, and robust cybersecurity measures. Understanding these complex challenges and adapting the synergistic utilization of cutting-edge technologies are becoming increasingly necessary. Human Impact on Security and Privacy: Network and Human Security, Social Media, and Devices provides a global perspective on current and future trends concerning the integration of intelligent systems with cybersecurity applications. It offers a comprehensive exploration of ethical considerations within the realms of security, artificial intelligence, agriculture, and data science. Covering topics such as the evolving landscape of cybersecurity, social engineering perspectives, and algorithmic transparency, this publication is particularly valuable for researchers, industry professionals, academics, and policymakers in fields such as agriculture, cybersecurity, AI, data science, computer science, and ethics.

The Handbook of Research on AI and ML for Intelligent Machines and Systems offers a comprehensive exploration of the pivotal role played by artificial intelligence (AI) and machine learning (ML) technologies in the development of intelligent machines. As the demand for intelligent machines continues to rise across various sectors, understanding the integration of these advanced technologies becomes paramount. While AI and ML have individually showcased their capabilities in developing robust intelligent machine systems and services, their fusion holds the key to propelling intelligent machines to a new realm of transformation. By compiling recent advancements in intelligent machines that rely on machine learning and deep learning technologies, this book serves as a vital resource for researchers, graduate students, PhD scholars, faculty members, scientists, and software developers. It offers valuable insights into the key concepts of AI and ML, covering essential security aspects, current trends, and often overlooked perspectives that are crucial for achieving comprehensive understanding. It not only explores the theoretical foundations of AI and ML but also provides guidance on applying these techniques to solve real-world problems. Unlike traditional texts, it offers flexibility through its distinctive module-based structure, allowing readers to follow their own learning paths.

Machine learning (ML) and the internet of things (IoT) are the top technologies used by businesses to increase efficiency, productivity, and competitiveness in this fast-paced digital era transformation. ML is the key tool for fast processing and decision making applied to smart city applications and next-generation IoT devices, which require ML to satisfy their working objective. IoT technology has proven efficient in solving many real-world problems, and ML algorithms combined with IoT means the fusion of product and intelligence to achieve better automation, efficiency, productivity, and connectivity. The Handbook of Research on Machine Learning-Enabled IoT for Smart Applications Across Industries highlights the importance of ML for IoT’s success and diverse ML-powered IoT applications. This book addresses the problems and challenges in energy, industry, and healthcare and solutions proposed for ML-enabled IoT and new algorithms in ML. It further addresses their accuracy for existing real-time applications. Covering topics such as agriculture, pattern recognition, and smart applications, this premier reference source is an essential resource for engineers, scientists, educators, students, researchers, and academicians.

New technologies like blockchain and Internet of Things (IoT) are constantly improving the state-of-the-art in healthcare services. The trend of keeping medical records in digital formats is also increasing the reliance of modern healthcare service providers on these new technologies. This edited book brings a collection of reviews on blockchain and IoT technologies that are driving innovation in digital and smart healthcare systems. The editors bring an academic and practical approach to assist professionals and readers in understanding computerized healthcare solutions. 16 referenced chapters provide knowledge about fundamental framework, research insights, and empirical evidence for effective smart healthcare applications. The chapters also cover benefits and challenges of specific smart health frameworks, giving an informative overview of the subject. Key themes of the book include: 1. Technological Foundations for Smart Healthcare 2. Blockchain Applications in Healthcare 3. Internet of Things (IoT) in Healthcare 4. Artificial Intelligence (AI) Integration 5. Security, Privacy, and Authentication 6. Medical Imaging and Deep Learning 7. Telemedicine The content in the book is designed to help administrators and healthcare professionals to understand the basics of blockchain tech and IoT in smart healthcare systems and strengthen the competitive advantage of their clinics.

This book highlights authentication and trust evaluation models in the Industrial Internet of Things. It further discusses data breaches and security issues in various Artificial Intelligence-enabled systems and uses Blockchain to resolve the challenges faced by the Industrial Internet of Things. The text showcases performance quality assessment for the Industrial Internet of Things’ applications. This book: Discusses and evaluates different quality assessment systems and authentication of smart devices Addresses data handling, data security, confidentiality, and integrity of data in the Industrial Internet of Things Focuses on developing framework and standardization of quality assessment for diverse Internet of Things-enabled devices Explains the designing, developing, and framing of smart machines, that are equipped with tools for tracking and logging data to provide advanced security features Presents the convergence of the Internet of Things toward Industry 4.0 through quality assessment via analyzing data security and identifying vulnerabilities It is primarily written for graduate students and academic researchers in the fields of electrical engineering, electronics, and communications engineering, industrial and production engineering, computer science, and engineering.

This book presents the outcome of two-day 2nd International e-Conference on Sustainable and Innovative Solutions for Current Challenges in Engineering and Technology (ICSISCET 2020) held at Madhav Institute of Technology & Science (MITS), Gwalior, India, from December 18–19, 2020. The book extensively covers recent research in artificial intelligence (AI) that knit together nature-inspired algorithms, evolutionary computing, fuzzy systems, computational intelligence, machine learning, deep learning, etc., which is very useful while dealing with real problems due to their model-free structure, learning ability, and flexible approach. These techniques mimic human thinking and decision-making abilities to produce systems that are intelligent, efficient, cost-effective, and fast. The book provides a friendly and informative treatment of the topics which makes this book an ideal reference for both beginners and experienced researchers.