Intelligent Edge Computing for Cyber Physical Applications introduces state-of-the-art research methodologies, tools and techniques, challenges, and solutions with further research opportunities in the area of edge-based cyber-physical systems. The book presents a comprehensive review of recent literature and analysis of different techniques for building edge-based CPS. In addition, it describes how edge-based CPS can be built to seamlessly interact with physical machines for optimal performance, covering various aspects of edge computing architectures for dynamic resource provisioning, mobile edge computing, energy saving scenarios, and different security issues.

Sections feature practical use cases of edge-computing which will help readers understand the workings of edge-based systems in detail, taking into account the need to present intellectual challenges while appealing to a broad readership, including academic researchers, practicing engineers and managers, and graduate students.

This is a monumental reference for the theory and practice of computer security. Comprehensive in scope, this text covers applied and practical elements, theory, and the reasons for the design of applications and security techniques. It covers both the management and the engineering issues of computer security. It provides excellent examples of ideas and mechanisms that demonstrate how disparate techniques and principles are combined in widely-used systems. This book is acclaimed for its scope, clear and lucid writing, and its combination of formal and theoretical aspects with real systems, technologies, techniques, and policies.

This is a monumental reference for the theory and practice of computer security. Comprehensive in scope, this text covers applied and practical elements, theory, and the reasons for the design of applications and security techniques. It covers both the management and the engineering issues of computer security. It provides excellent examples of ideas and mechanisms that demonstrate how disparate techniques and principles are combined in widely-used systems. This book is acclaimed for its scope, clear and lucid writing, and its combination of formal and theoretical aspects with real systems, technologies, techniques, and policies.

While Computer Security is a broader term which incorporates technologies, protocols, standards and policies to ensure the security of the computing systems including the computer hardware, software and the information stored in it, Cyber Security is a specific, growing field to protect computer networks (offline and online) from unauthorized access, botnets, phishing scams, etc. Machine learning is a branch of Computer Science which enables computing machines to adopt new behaviors on the basis of observable and verifiable data and information. It can be applied to ensure the security of the computers and the information by detecting anomalies using data mining and other such techniques.

This book will be an invaluable resource to understand the importance of machine learning and data mining in establishing computer and cyber security. It emphasizes important security aspects associated with computer and cyber security along with the analysis of machine learning and data mining based solutions. The book also highlights the future research domains in which these solutions can be applied. Furthermore, it caters to the needs of IT professionals, researchers, faculty members, scientists, graduate students, research scholars and software developers who seek to carry out research and develop combating solutions in the area of cyber security using machine learning based approaches. It is an extensive source of information for the readers belonging to the field of Computer Science and Engineering, and Cyber Security professionals.

Key Features:

While Computer Security is a broader term which incorporates technologies, protocols, standards and policies to ensure the security of the computing systems including the computer hardware, software and the information stored in it, Cyber Security is a specific, growing field to protect computer networks (offline and online) from unauthorized access, botnets, phishing scams, etc. Machine learning is a branch of Computer Science which enables computing machines to adopt new behaviors on the basis of observable and verifiable data and information. It can be applied to ensure the security of the computers and the information by detecting anomalies using data mining and other such techniques.

This book will be an invaluable resource to understand the importance of machine learning and data mining in establishing computer and cyber security. It emphasizes important security aspects associated with computer and cyber security along with the analysis of machine learning and data mining based solutions. The book also highlights the future research domains in which these solutions can be applied. Furthermore, it caters to the needs of IT professionals, researchers, faculty members, scientists, graduate students, research scholars and software developers who seek to carry out research and develop combating solutions in the area of cyber security using machine learning based approaches. It is an extensive source of information for the readers belonging to the field of Computer Science and Engineering, and Cyber Security professionals.

Key Features:

A Beginner’s Guide to Internet of Things Security focuses on security issues and developments in the Internet of Things (IoT) environment. The wide-ranging applications of IoT, including home appliances, transportation, logistics, healthcare, and smart cities, necessitate security applications that can be applied to every domain with minimal cost.

IoT contains three layers: application layer, middleware layer, and perception layer. The security problems of each layer are analyzed separately to identify solutions, along with the integration and scalability issues with the cross-layer architecture of IoT. The book discusses the state-of-the-art authentication-based security schemes, which can secure radio frequency identification (RFID) tags, along with some security models that are used to verify whether an authentication scheme is secure against any potential security risks. It also looks at existing authentication schemes and security models with their strengths and weaknesses. The book uses statistical and analytical data and explains its impact on the IoT field, as well as an extensive literature survey focusing on trust and privacy problems.

The open challenges and future research direction discussed in this book will help to further academic researchers and industry professionals in the domain of security.

Dr. Brij B. Gupta is an assistant professor in the Department of Computer Engineering, National Institute of Technology, Kurukshetra, India.

Ms. Aakanksha Tewari is a PhD Scholar in the Department of Computer Engineering, National Institute of Technology, Kurukshetra, India.

A Beginner’s Guide to Internet of Things Security focuses on security issues and developments in the Internet of Things (IoT) environment. The wide-ranging applications of IoT, including home appliances, transportation, logistics, healthcare, and smart cities, necessitate security applications that can be applied to every domain with minimal cost.

IoT contains three layers: application layer, middleware layer, and perception layer. The security problems of each layer are analyzed separately to identify solutions, along with the integration and scalability issues with the cross-layer architecture of IoT. The book discusses the state-of-the-art authentication-based security schemes, which can secure radio frequency identification (RFID) tags, along with some security models that are used to verify whether an authentication scheme is secure against any potential security risks. It also looks at existing authentication schemes and security models with their strengths and weaknesses. The book uses statistical and analytical data and explains its impact on the IoT field, as well as an extensive literature survey focusing on trust and privacy problems.

The open challenges and future research direction discussed in this book will help to further academic researchers and industry professionals in the domain of security.

Dr. Brij B. Gupta is an assistant professor in the Department of Computer Engineering, National Institute of Technology, Kurukshetra, India.

Ms. Aakanksha Tewari is a PhD Scholar in the Department of Computer Engineering, National Institute of Technology, Kurukshetra, India.

Intelligent Edge Computing for Cyber Physical Applications introduces state-of-the-art research methodologies, tools and techniques, challenges, and solutions with further research opportunities in the area of edge-based cyber-physical systems. The book presents a comprehensive review of recent literature and analysis of different techniques for building edge-based CPS. In addition, it describes how edge-based CPS can be built to seamlessly interact with physical machines for optimal performance, covering various aspects of edge computing architectures for dynamic resource provisioning, mobile edge computing, energy saving scenarios, and different security issues.

Sections feature practical use cases of edge-computing which will help readers understand the workings of edge-based systems in detail, taking into account the need to present intellectual challenges while appealing to a broad readership, including academic researchers, practicing engineers and managers, and graduate students.

This is a monumental reference for the theory and practice of computer security. Comprehensive in scope, this text covers applied and practical elements, theory, and the reasons for the design of applications and security techniques. It covers both the management and the engineering issues of computer security. It provides excellent examples of ideas and mechanisms that demonstrate how disparate techniques and principles are combined in widely-used systems. This book is acclaimed for its scope, clear and lucid writing, and its combination of formal and theoretical aspects with real systems, technologies, techniques, and policies.

This is a monumental reference for the theory and practice of computer security. Comprehensive in scope, this text covers applied and practical elements, theory, and the reasons for the design of applications and security techniques. It covers both the management and the engineering issues of computer security. It provides excellent examples of ideas and mechanisms that demonstrate how disparate techniques and principles are combined in widely-used systems. This book is acclaimed for its scope, clear and lucid writing, and its combination of formal and theoretical aspects with real systems, technologies, techniques, and policies.

While Computer Security is a broader term which incorporates technologies, protocols, standards and policies to ensure the security of the computing systems including the computer hardware, software and the information stored in it, Cyber Security is a specific, growing field to protect computer networks (offline and online) from unauthorized access, botnets, phishing scams, etc. Machine learning is a branch of Computer Science which enables computing machines to adopt new behaviors on the basis of observable and verifiable data and information. It can be applied to ensure the security of the computers and the information by detecting anomalies using data mining and other such techniques.

This book will be an invaluable resource to understand the importance of machine learning and data mining in establishing computer and cyber security. It emphasizes important security aspects associated with computer and cyber security along with the analysis of machine learning and data mining based solutions. The book also highlights the future research domains in which these solutions can be applied. Furthermore, it caters to the needs of IT professionals, researchers, faculty members, scientists, graduate students, research scholars and software developers who seek to carry out research and develop combating solutions in the area of cyber security using machine learning based approaches. It is an extensive source of information for the readers belonging to the field of Computer Science and Engineering, and Cyber Security professionals.

Key Features:

While Computer Security is a broader term which incorporates technologies, protocols, standards and policies to ensure the security of the computing systems including the computer hardware, software and the information stored in it, Cyber Security is a specific, growing field to protect computer networks (offline and online) from unauthorized access, botnets, phishing scams, etc. Machine learning is a branch of Computer Science which enables computing machines to adopt new behaviors on the basis of observable and verifiable data and information. It can be applied to ensure the security of the computers and the information by detecting anomalies using data mining and other such techniques.

This book will be an invaluable resource to understand the importance of machine learning and data mining in establishing computer and cyber security. It emphasizes important security aspects associated with computer and cyber security along with the analysis of machine learning and data mining based solutions. The book also highlights the future research domains in which these solutions can be applied. Furthermore, it caters to the needs of IT professionals, researchers, faculty members, scientists, graduate students, research scholars and software developers who seek to carry out research and develop combating solutions in the area of cyber security using machine learning based approaches. It is an extensive source of information for the readers belonging to the field of Computer Science and Engineering, and Cyber Security professionals.

Key Features:

A Beginner’s Guide to Internet of Things Security focuses on security issues and developments in the Internet of Things (IoT) environment. The wide-ranging applications of IoT, including home appliances, transportation, logistics, healthcare, and smart cities, necessitate security applications that can be applied to every domain with minimal cost.

IoT contains three layers: application layer, middleware layer, and perception layer. The security problems of each layer are analyzed separately to identify solutions, along with the integration and scalability issues with the cross-layer architecture of IoT. The book discusses the state-of-the-art authentication-based security schemes, which can secure radio frequency identification (RFID) tags, along with some security models that are used to verify whether an authentication scheme is secure against any potential security risks. It also looks at existing authentication schemes and security models with their strengths and weaknesses. The book uses statistical and analytical data and explains its impact on the IoT field, as well as an extensive literature survey focusing on trust and privacy problems.

The open challenges and future research direction discussed in this book will help to further academic researchers and industry professionals in the domain of security.

Dr. Brij B. Gupta is an assistant professor in the Department of Computer Engineering, National Institute of Technology, Kurukshetra, India.

Ms. Aakanksha Tewari is a PhD Scholar in the Department of Computer Engineering, National Institute of Technology, Kurukshetra, India.

A Beginner’s Guide to Internet of Things Security focuses on security issues and developments in the Internet of Things (IoT) environment. The wide-ranging applications of IoT, including home appliances, transportation, logistics, healthcare, and smart cities, necessitate security applications that can be applied to every domain with minimal cost.

IoT contains three layers: application layer, middleware layer, and perception layer. The security problems of each layer are analyzed separately to identify solutions, along with the integration and scalability issues with the cross-layer architecture of IoT. The book discusses the state-of-the-art authentication-based security schemes, which can secure radio frequency identification (RFID) tags, along with some security models that are used to verify whether an authentication scheme is secure against any potential security risks. It also looks at existing authentication schemes and security models with their strengths and weaknesses. The book uses statistical and analytical data and explains its impact on the IoT field, as well as an extensive literature survey focusing on trust and privacy problems.

The open challenges and future research direction discussed in this book will help to further academic researchers and industry professionals in the domain of security.

Dr. Brij B. Gupta is an assistant professor in the Department of Computer Engineering, National Institute of Technology, Kurukshetra, India.

Ms. Aakanksha Tewari is a PhD Scholar in the Department of Computer Engineering, National Institute of Technology, Kurukshetra, India.