This book focuses on the key technologies, challenges, and research directions of the Industrial Internet of Things (IIoT). It provides a basis for discussing open principles, methods, and research problems, and provides a systematic overview of the state-of-the-art research efforts, directions, and potential challenges associated with IIoT.

Industrial Internet of Things: Technologies and Research Directions covers how industry automation is projected to be the largest and fastest-growing segment of the market. It explores the collaborative development of high-performance telecommunications, military, industrial, and general-purpose embedded computing applications, and offers a systematic overview of the state-of-the-art research efforts and new potential directions.

Researchers, academicians, and professionals working in this inter-disciplinary area will be interested in this book.

This book focuses on the key technologies, challenges, and research directions of the Industrial Internet of Things (IIoT). It provides a basis for discussing open principles, methods, and research problems, and provides a systematic overview of the state-of-the-art research efforts, directions, and potential challenges associated with IIoT.

Industrial Internet of Things: Technologies and Research Directions covers how industry automation is projected to be the largest and fastest-growing segment of the market. It explores the collaborative development of high-performance telecommunications, military, industrial, and general-purpose embedded computing applications, and offers a systematic overview of the state-of-the-art research efforts and new potential directions.

Researchers, academicians, and professionals working in this inter-disciplinary area will be interested in this book.

An Interdisciplinary Approach to Modern Network Security presents the latest methodologies and trends in detecting and preventing network threats. Investigating the potential of current and emerging security technologies, this publication is an all-inclusive reference source for academicians, researchers, students, professionals, practitioners, network analysts and technology specialists interested in the simulation and application of computer network protection. It presents theoretical frameworks and the latest research findings in network security technologies, while analyzing malicious threats which can compromise network integrity. It discusses the security and optimization of computer networks for use in a variety of disciplines and fields.

Touching on such matters as mobile and VPN security, IP spoofing and intrusion detection, this edited collection emboldens the efforts of researchers, academics and network administrators working in both the public and private sectors. This edited compilation includes chapters covering topics such as attacks and countermeasures, mobile wireless networking, intrusion detection systems, next-generation firewalls, web security and much more.

Information and communication systems are an essential component of our society, forcing us to become dependent on these infrastructures. At the same time, these systems are undergoing a convergence and interconnection process that has its benefits, but also raises specific threats to user interests. Citizens and organizations must feel safe when using cyberspace facilities in order to benefit from its advantages. This book is interdisciplinary in the sense that it covers a wide range of topics like network security threats, attacks, tools and procedures to mitigate the effects of malware and common network attacks, network security architecture and deep learning methods of intrusion detection.

An Interdisciplinary Approach to Modern Network Security presents the latest methodologies and trends in detecting and preventing network threats. Investigating the potential of current and emerging security technologies, this publication is an all-inclusive reference source for academicians, researchers, students, professionals, practitioners, network analysts and technology specialists interested in the simulation and application of computer network protection. It presents theoretical frameworks and the latest research findings in network security technologies, while analyzing malicious threats which can compromise network integrity. It discusses the security and optimization of computer networks for use in a variety of disciplines and fields.

Touching on such matters as mobile and VPN security, IP spoofing and intrusion detection, this edited collection emboldens the efforts of researchers, academics and network administrators working in both the public and private sectors. This edited compilation includes chapters covering topics such as attacks and countermeasures, mobile wireless networking, intrusion detection systems, next-generation firewalls, web security and much more.

Information and communication systems are an essential component of our society, forcing us to become dependent on these infrastructures. At the same time, these systems are undergoing a convergence and interconnection process that has its benefits, but also raises specific threats to user interests. Citizens and organizations must feel safe when using cyberspace facilities in order to benefit from its advantages. This book is interdisciplinary in the sense that it covers a wide range of topics like network security threats, attacks, tools and procedures to mitigate the effects of malware and common network attacks, network security architecture and deep learning methods of intrusion detection.

This new volume features new and innovative research on the positive contributions of IoT and cloud technology in healthcare information systems for the improvement of patient care and disease management, highlighting the challenges and difficulties along with solutions and strategies. The authors focus on theories, systems, methods, algorithms, and applications and showcase the interface between e-health and communication technologies and their beneficial contribution to building efficient and secure healthcare information systems.

Healthcare information systems involve data generation, compilation, arrangement, examination and synthesis, and communication and use. This incorporates frameworks that gather, store, maintain, and protect patients’ electronic medical information and records, providing an invaluable resource for supporting medical services strategies and choices. This volume discusses a multitude of diverse new information technologies in telemedicine, in security for healthcare systems, for medical image authentication, in pulse oximetry via Bluetooth, for virus detection via smartphones, for tumor extraction via extreme learning machine and k-means clustering, for the detection of cancerous cells, for music therapy for mental health purposes, and much more.

This new volume features new and innovative research on the positive contributions of IoT and cloud technology in healthcare information systems for the improvement of patient care and disease management, highlighting the challenges and difficulties along with solutions and strategies. The authors focus on theories, systems, methods, algorithms, and applications and showcase the interface between e-health and communication technologies and their beneficial contribution to building efficient and secure healthcare information systems.

Healthcare information systems involve data generation, compilation, arrangement, examination and synthesis, and communication and use. This incorporates frameworks that gather, store, maintain, and protect patients’ electronic medical information and records, providing an invaluable resource for supporting medical services strategies and choices. This volume discusses a multitude of diverse new information technologies in telemedicine, in security for healthcare systems, for medical image authentication, in pulse oximetry via Bluetooth, for virus detection via smartphones, for tumor extraction via extreme learning machine and k-means clustering, for the detection of cancerous cells, for music therapy for mental health purposes, and much more.

Written and edited by a team of experts in the field, this collection of papers reflects the most up-to-date and comprehensive current state of machine learning and data science for industry, government, and academia.

Machine learning (ML) and data science (DS) are very active topics with an extensive scope, both in terms of theory and applications. They have been established as an important emergent scientific field and paradigm driving research evolution in such disciplines as statistics, computing science and intelligence science, and practical transformation in such domains as science, engineering, the public sector, business, social science, and lifestyle. Simultaneously, their applications provide important challenges that can often be addressed only with innovative machine learning and data science algorithms.

These algorithms encompass the larger areas of artificial intelligence, data analytics, machine learning, pattern recognition, natural language understanding, and big data manipulation. They also tackle related new scientific challenges, ranging from data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization, to integrative analysis across heterogeneous and interdependent complex resources for better decision-making, collaboration, and, ultimately, value creation.

Written and edited by a team of experts in the field, this collection of papers reflects the most up-to-date and comprehensive current state of machine learning and data science for industry, government, and academia.

Machine learning (ML) and data science (DS) are very active topics with an extensive scope, both in terms of theory and applications. They have been established as an important emergent scientific field and paradigm driving research evolution in such disciplines as statistics, computing science and intelligence science, and practical transformation in such domains as science, engineering, the public sector, business, social science, and lifestyle. Simultaneously, their applications provide important challenges that can often be addressed only with innovative machine learning and data science algorithms.

These algorithms encompass the larger areas of artificial intelligence, data analytics, machine learning, pattern recognition, natural language understanding, and big data manipulation. They also tackle related new scientific challenges, ranging from data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization, to integrative analysis across heterogeneous and interdependent complex resources for better decision-making, collaboration, and, ultimately, value creation.

TRUST-BASED COMMUNICATION SYSTEMS FOR INTERNET OF THINGS APPLICATIONS

Highlighting the challenges and difficulties in implementing trust-based communication systems for Internet of Things (IoT) services and applications, this innovative new volume is a critical reference source for academics, professionals, engineers, technology designers, analysts, and students.

The primary objective of this edited book is to deliver technologies to improve trust and eliminate malicious actors in participatory exchanges throughout communication using Internet of Things (IOT) devices such that these methods should not only be able to identify bad actors but also to improve communication and trust in the environment without violating object privacy. Whether as a reference for the engineer or scientist or a textbook for the student, this is a must-have for any library.

TRUST-BASED COMMUNICATION SYSTEMS FOR INTERNET OF THINGS APPLICATIONS

Highlighting the challenges and difficulties in implementing trust-based communication systems for Internet of Things (IoT) services and applications, this innovative new volume is a critical reference source for academics, professionals, engineers, technology designers, analysts, and students.

The primary objective of this edited book is to deliver technologies to improve trust and eliminate malicious actors in participatory exchanges throughout communication using Internet of Things (IOT) devices such that these methods should not only be able to identify bad actors but also to improve communication and trust in the environment without violating object privacy. Whether as a reference for the engineer or scientist or a textbook for the student, this is a must-have for any library.

Knowledge Engineering (KE) is a field within artificial intelligence that develops knowledgebased systems. KE is the process of imitating how a human expert in a specific domain would act and take decisions. It contains large amounts of knowledge, like metadata and information about a data object that describes characteristics such as content, quality, and format, structure and processes. Such systems are computer programs that are the basis of how a decision is made or a conclusion is reached. It is having all the rules and reasoning mechanisms to provide solutions to real-world problems. This book presents an extensive collection of the recent findings and innovative research in the information system and KE domain. Highlighting the challenges and difficulties in implementing these approaches, this book is a critical reference source for academicians, professionals, engineers, technology designers, analysts, undergraduate and postgraduate students in computing science and related disciplines such as Information systems, Knowledge Engineering, Intelligent Systems, Artifi cial Intelligence, Cognitive Neuro - science, and Robotics. In addition, anyone who is interested or involved in sophisticated information systems and knowledge engineering developments will find this book a valuable source of ideas and guidance.

Knowledge Engineering (KE) is a field within artificial intelligence that develops knowledgebased systems. KE is the process of imitating how a human expert in a specific domain would act and take decisions. It contains large amounts of knowledge, like metadata and information about a data object that describes characteristics such as content, quality, and format, structure and processes. Such systems are computer programs that are the basis of how a decision is made or a conclusion is reached. It is having all the rules and reasoning mechanisms to provide solutions to real-world problems. This book presents an extensive collection of the recent findings and innovative research in the information system and KE domain. Highlighting the challenges and difficulties in implementing these approaches, this book is a critical reference source for academicians, professionals, engineers, technology designers, analysts, undergraduate and postgraduate students in computing science and related disciplines such as Information systems, Knowledge Engineering, Intelligent Systems, Artifi cial Intelligence, Cognitive Neuro - science, and Robotics. In addition, anyone who is interested or involved in sophisticated information systems and knowledge engineering developments will find this book a valuable source of ideas and guidance.

This book focuses on the key technologies, challenges, and research directions of the Industrial Internet of Things (IIoT). It provides a basis for discussing open principles, methods, and research problems, and provides a systematic overview of the state-of-the-art research efforts, directions, and potential challenges associated with IIoT.

Industrial Internet of Things: Technologies and Research Directions covers how industry automation is projected to be the largest and fastest-growing segment of the market. It explores the collaborative development of high-performance telecommunications, military, industrial, and general-purpose embedded computing applications, and offers a systematic overview of the state-of-the-art research efforts and new potential directions.

Researchers, academicians, and professionals working in this inter-disciplinary area will be interested in this book.

This book focuses on the key technologies, challenges, and research directions of the Industrial Internet of Things (IIoT). It provides a basis for discussing open principles, methods, and research problems, and provides a systematic overview of the state-of-the-art research efforts, directions, and potential challenges associated with IIoT.

Industrial Internet of Things: Technologies and Research Directions covers how industry automation is projected to be the largest and fastest-growing segment of the market. It explores the collaborative development of high-performance telecommunications, military, industrial, and general-purpose embedded computing applications, and offers a systematic overview of the state-of-the-art research efforts and new potential directions.

Researchers, academicians, and professionals working in this inter-disciplinary area will be interested in this book.

An Interdisciplinary Approach to Modern Network Security presents the latest methodologies and trends in detecting and preventing network threats. Investigating the potential of current and emerging security technologies, this publication is an all-inclusive reference source for academicians, researchers, students, professionals, practitioners, network analysts and technology specialists interested in the simulation and application of computer network protection. It presents theoretical frameworks and the latest research findings in network security technologies, while analyzing malicious threats which can compromise network integrity. It discusses the security and optimization of computer networks for use in a variety of disciplines and fields.

Touching on such matters as mobile and VPN security, IP spoofing and intrusion detection, this edited collection emboldens the efforts of researchers, academics and network administrators working in both the public and private sectors. This edited compilation includes chapters covering topics such as attacks and countermeasures, mobile wireless networking, intrusion detection systems, next-generation firewalls, web security and much more.

Information and communication systems are an essential component of our society, forcing us to become dependent on these infrastructures. At the same time, these systems are undergoing a convergence and interconnection process that has its benefits, but also raises specific threats to user interests. Citizens and organizations must feel safe when using cyberspace facilities in order to benefit from its advantages. This book is interdisciplinary in the sense that it covers a wide range of topics like network security threats, attacks, tools and procedures to mitigate the effects of malware and common network attacks, network security architecture and deep learning methods of intrusion detection.

An Interdisciplinary Approach to Modern Network Security presents the latest methodologies and trends in detecting and preventing network threats. Investigating the potential of current and emerging security technologies, this publication is an all-inclusive reference source for academicians, researchers, students, professionals, practitioners, network analysts and technology specialists interested in the simulation and application of computer network protection. It presents theoretical frameworks and the latest research findings in network security technologies, while analyzing malicious threats which can compromise network integrity. It discusses the security and optimization of computer networks for use in a variety of disciplines and fields.

Touching on such matters as mobile and VPN security, IP spoofing and intrusion detection, this edited collection emboldens the efforts of researchers, academics and network administrators working in both the public and private sectors. This edited compilation includes chapters covering topics such as attacks and countermeasures, mobile wireless networking, intrusion detection systems, next-generation firewalls, web security and much more.

Information and communication systems are an essential component of our society, forcing us to become dependent on these infrastructures. At the same time, these systems are undergoing a convergence and interconnection process that has its benefits, but also raises specific threats to user interests. Citizens and organizations must feel safe when using cyberspace facilities in order to benefit from its advantages. This book is interdisciplinary in the sense that it covers a wide range of topics like network security threats, attacks, tools and procedures to mitigate the effects of malware and common network attacks, network security architecture and deep learning methods of intrusion detection.

This new volume features new and innovative research on the positive contributions of IoT and cloud technology in healthcare information systems for the improvement of patient care and disease management, highlighting the challenges and difficulties along with solutions and strategies. The authors focus on theories, systems, methods, algorithms, and applications and showcase the interface between e-health and communication technologies and their beneficial contribution to building efficient and secure healthcare information systems.

Healthcare information systems involve data generation, compilation, arrangement, examination and synthesis, and communication and use. This incorporates frameworks that gather, store, maintain, and protect patients’ electronic medical information and records, providing an invaluable resource for supporting medical services strategies and choices. This volume discusses a multitude of diverse new information technologies in telemedicine, in security for healthcare systems, for medical image authentication, in pulse oximetry via Bluetooth, for virus detection via smartphones, for tumor extraction via extreme learning machine and k-means clustering, for the detection of cancerous cells, for music therapy for mental health purposes, and much more.

This new volume features new and innovative research on the positive contributions of IoT and cloud technology in healthcare information systems for the improvement of patient care and disease management, highlighting the challenges and difficulties along with solutions and strategies. The authors focus on theories, systems, methods, algorithms, and applications and showcase the interface between e-health and communication technologies and their beneficial contribution to building efficient and secure healthcare information systems.

Healthcare information systems involve data generation, compilation, arrangement, examination and synthesis, and communication and use. This incorporates frameworks that gather, store, maintain, and protect patients’ electronic medical information and records, providing an invaluable resource for supporting medical services strategies and choices. This volume discusses a multitude of diverse new information technologies in telemedicine, in security for healthcare systems, for medical image authentication, in pulse oximetry via Bluetooth, for virus detection via smartphones, for tumor extraction via extreme learning machine and k-means clustering, for the detection of cancerous cells, for music therapy for mental health purposes, and much more.

Written and edited by a team of experts in the field, this collection of papers reflects the most up-to-date and comprehensive current state of machine learning and data science for industry, government, and academia.

Machine learning (ML) and data science (DS) are very active topics with an extensive scope, both in terms of theory and applications. They have been established as an important emergent scientific field and paradigm driving research evolution in such disciplines as statistics, computing science and intelligence science, and practical transformation in such domains as science, engineering, the public sector, business, social science, and lifestyle. Simultaneously, their applications provide important challenges that can often be addressed only with innovative machine learning and data science algorithms.

These algorithms encompass the larger areas of artificial intelligence, data analytics, machine learning, pattern recognition, natural language understanding, and big data manipulation. They also tackle related new scientific challenges, ranging from data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization, to integrative analysis across heterogeneous and interdependent complex resources for better decision-making, collaboration, and, ultimately, value creation.

Written and edited by a team of experts in the field, this collection of papers reflects the most up-to-date and comprehensive current state of machine learning and data science for industry, government, and academia.

Machine learning (ML) and data science (DS) are very active topics with an extensive scope, both in terms of theory and applications. They have been established as an important emergent scientific field and paradigm driving research evolution in such disciplines as statistics, computing science and intelligence science, and practical transformation in such domains as science, engineering, the public sector, business, social science, and lifestyle. Simultaneously, their applications provide important challenges that can often be addressed only with innovative machine learning and data science algorithms.

These algorithms encompass the larger areas of artificial intelligence, data analytics, machine learning, pattern recognition, natural language understanding, and big data manipulation. They also tackle related new scientific challenges, ranging from data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization, to integrative analysis across heterogeneous and interdependent complex resources for better decision-making, collaboration, and, ultimately, value creation.

TRUST-BASED COMMUNICATION SYSTEMS FOR INTERNET OF THINGS APPLICATIONS

Highlighting the challenges and difficulties in implementing trust-based communication systems for Internet of Things (IoT) services and applications, this innovative new volume is a critical reference source for academics, professionals, engineers, technology designers, analysts, and students.

The primary objective of this edited book is to deliver technologies to improve trust and eliminate malicious actors in participatory exchanges throughout communication using Internet of Things (IOT) devices such that these methods should not only be able to identify bad actors but also to improve communication and trust in the environment without violating object privacy. Whether as a reference for the engineer or scientist or a textbook for the student, this is a must-have for any library.

TRUST-BASED COMMUNICATION SYSTEMS FOR INTERNET OF THINGS APPLICATIONS

Highlighting the challenges and difficulties in implementing trust-based communication systems for Internet of Things (IoT) services and applications, this innovative new volume is a critical reference source for academics, professionals, engineers, technology designers, analysts, and students.

The primary objective of this edited book is to deliver technologies to improve trust and eliminate malicious actors in participatory exchanges throughout communication using Internet of Things (IOT) devices such that these methods should not only be able to identify bad actors but also to improve communication and trust in the environment without violating object privacy. Whether as a reference for the engineer or scientist or a textbook for the student, this is a must-have for any library.

Knowledge Engineering (KE) is a field within artificial intelligence that develops knowledgebased systems. KE is the process of imitating how a human expert in a specific domain would act and take decisions. It contains large amounts of knowledge, like metadata and information about a data object that describes characteristics such as content, quality, and format, structure and processes. Such systems are computer programs that are the basis of how a decision is made or a conclusion is reached. It is having all the rules and reasoning mechanisms to provide solutions to real-world problems. This book presents an extensive collection of the recent findings and innovative research in the information system and KE domain. Highlighting the challenges and difficulties in implementing these approaches, this book is a critical reference source for academicians, professionals, engineers, technology designers, analysts, undergraduate and postgraduate students in computing science and related disciplines such as Information systems, Knowledge Engineering, Intelligent Systems, Artifi cial Intelligence, Cognitive Neuro - science, and Robotics. In addition, anyone who is interested or involved in sophisticated information systems and knowledge engineering developments will find this book a valuable source of ideas and guidance.

Knowledge Engineering (KE) is a field within artificial intelligence that develops knowledgebased systems. KE is the process of imitating how a human expert in a specific domain would act and take decisions. It contains large amounts of knowledge, like metadata and information about a data object that describes characteristics such as content, quality, and format, structure and processes. Such systems are computer programs that are the basis of how a decision is made or a conclusion is reached. It is having all the rules and reasoning mechanisms to provide solutions to real-world problems. This book presents an extensive collection of the recent findings and innovative research in the information system and KE domain. Highlighting the challenges and difficulties in implementing these approaches, this book is a critical reference source for academicians, professionals, engineers, technology designers, analysts, undergraduate and postgraduate students in computing science and related disciplines such as Information systems, Knowledge Engineering, Intelligent Systems, Artifi cial Intelligence, Cognitive Neuro - science, and Robotics. In addition, anyone who is interested or involved in sophisticated information systems and knowledge engineering developments will find this book a valuable source of ideas and guidance.