Dac-Nhuong Le – författare

IOT: Security and Privacy Paradigm covers the evolution of security and privacy issues in the Internet of Things (IoT). It focuses on bringing all security and privacy related technologies into one source, so that students, researchers, and practitioners can refer to this book for easy understanding of IoT security and privacy issues.

This edited book uses Security Engineering and Privacy-by-Design principles to design a secure IoT ecosystem and to implement cyber-security solutions. This book takes the readers on a journey that begins with understanding the security issues in IoT-enabled technologies and how it can be applied in various aspects. It walks readers through engaging with security challenges and builds a safe infrastructure for IoT devices. The book helps readers gain an understand of security architecture through IoT and describes the state of the art of IoT countermeasures. It also differentiates security threats in IoT-enabled infrastructure from traditional ad hoc or infrastructural networks, and provides a comprehensive discussion on the security challenges and solutions in RFID, WSNs, in IoT.

This book aims to provide the concepts of related technologies and novel findings of the researchers through its chapter organization. The primary audience includes specialists, researchers, graduate students, designers, experts and engineers who are focused on research and security related issues.

Souvik Pal, PhD, has worked as Assistant Professor in Nalanda Institute of Technology, Bhubaneswar, and JIS College of Engineering, Kolkata (NAAC "A" Accredited College). He is the organizing Chair and Plenary Speaker of RICE Conference in Vietnam; and organizing co-convener of ICICIT, Tunisia. He has served in many conferences as chair, keynote speaker, and he also chaired international conference sessions and presented session talks internationally. His research area includes Cloud Computing, Big Data, Wireless Sensor Network (WSN), Internet of Things, and Data Analytics.

Vicente García-Díaz, PhD, is an Associate Professor in the Department of Computer Science at the University of Oviedo (Languages and Computer Systems area). He is also the editor of several special issues in prestigious journals such as Scientific Programming and International Journal of Interactive Multimedia and Artificial Intelligence. His research interests include eLearning, machine learning and the use of domain specific languages in different areas.

Dac-Nhuong Le, PhD, is Deputy-Head of Faculty of Information Technology, and Vice-Director of Information Technology Apply and Foreign Language Training Center, Haiphong University, Vietnam. His area of research includes: evaluation computing and approximate algorithms, network communication, security and vulnerability, network performance analysis and simulation, cloud computing, IoT and image processing in biomedical. Presently, he is serving on the editorial board of several international journals and has authored nine computer science books published by Springer, Wiley, CRC Press, Lambert Publication, and Scholar Press.

IOT: Security and Privacy Paradigm covers the evolution of security and privacy issues in the Internet of Things (IoT). It focuses on bringing all security and privacy related technologies into one source, so that students, researchers, and practitioners can refer to this book for easy understanding of IoT security and privacy issues.

This edited book uses Security Engineering and Privacy-by-Design principles to design a secure IoT ecosystem and to implement cyber-security solutions. This book takes the readers on a journey that begins with understanding the security issues in IoT-enabled technologies and how it can be applied in various aspects. It walks readers through engaging with security challenges and builds a safe infrastructure for IoT devices. The book helps readers gain an understand of security architecture through IoT and describes the state of the art of IoT countermeasures. It also differentiates security threats in IoT-enabled infrastructure from traditional ad hoc or infrastructural networks, and provides a comprehensive discussion on the security challenges and solutions in RFID, WSNs, in IoT.

This book aims to provide the concepts of related technologies and novel findings of the researchers through its chapter organization. The primary audience includes specialists, researchers, graduate students, designers, experts and engineers who are focused on research and security related issues.

Souvik Pal, PhD, has worked as Assistant Professor in Nalanda Institute of Technology, Bhubaneswar, and JIS College of Engineering, Kolkata (NAAC "A" Accredited College). He is the organizing Chair and Plenary Speaker of RICE Conference in Vietnam; and organizing co-convener of ICICIT, Tunisia. He has served in many conferences as chair, keynote speaker, and he also chaired international conference sessions and presented session talks internationally. His research area includes Cloud Computing, Big Data, Wireless Sensor Network (WSN), Internet of Things, and Data Analytics.

Vicente García-Díaz, PhD, is an Associate Professor in the Department of Computer Science at the University of Oviedo (Languages and Computer Systems area). He is also the editor of several special issues in prestigious journals such as Scientific Programming and International Journal of Interactive Multimedia and Artificial Intelligence. His research interests include eLearning, machine learning and the use of domain specific languages in different areas.

Dac-Nhuong Le, PhD, is Deputy-Head of Faculty of Information Technology, and Vice-Director of Information Technology Apply and Foreign Language Training Center, Haiphong University, Vietnam. His area of research includes: evaluation computing and approximate algorithms, network communication, security and vulnerability, network performance analysis and simulation, cloud computing, IoT and image processing in biomedical. Presently, he is serving on the editorial board of several international journals and has authored nine computer science books published by Springer, Wiley, CRC Press, Lambert Publication, and Scholar Press.

Machine Learning for Healthcare: Handling and Managing Data provides in-depth information about handling and managing healthcare data through machine learning methods. This book expresses the long-standing challenges in healthcare informatics and provides rational explanations of how to deal with them.

Machine Learning for Healthcare: Handling and Managing Data provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of machine learning applications. These are illustrated in a case study which examines how chronic disease is being redefined through patient-led data learning and the Internet of Things. This text offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare. Readers will discover the ethical implications of machine learning in healthcare and the future of machine learning in population and patient health optimization. This book can also help assist in the creation of a machine learning model, performance evaluation, and the operationalization of its outcomes within organizations. It may appeal to computer science/information technology professionals and researchers working in the area of machine learning, and is especially applicable to the healthcare sector.

The features of this book include:

Machine Learning for Healthcare: Handling and Managing Data provides in-depth information about handling and managing healthcare data through machine learning methods. This book expresses the long-standing challenges in healthcare informatics and provides rational explanations of how to deal with them.

Machine Learning for Healthcare: Handling and Managing Data provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of machine learning applications. These are illustrated in a case study which examines how chronic disease is being redefined through patient-led data learning and the Internet of Things. This text offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare. Readers will discover the ethical implications of machine learning in healthcare and the future of machine learning in population and patient health optimization. This book can also help assist in the creation of a machine learning model, performance evaluation, and the operationalization of its outcomes within organizations. It may appeal to computer science/information technology professionals and researchers working in the area of machine learning, and is especially applicable to the healthcare sector.

The features of this book include:

The bright future of green IoT will change our tomorrow environment to become healthier and green, with very high quality of service that is socially, environmentally, and economically sustainable. This book covers the most recent advances in IoT, it discusses Smart City implementation, and offers both quantitative and qualitative research.

It focuses on greening things such as green communication and networking, green design and implementations, green IoT services and applications, energy saving strategies, integrated RFIDs and sensor networks, mobility and network management, the cooperation of homogeneous and heterogeneous networks, smart objects, and green localization.

This book with its wide range of related topics in IoT and Smart City, will be useful for graduate students, researchers, academicians, institutions, and professionals that are interested in exploring the areas of IoT and Smart City.

The bright future of green IoT will change our tomorrow environment to become healthier and green, with very high quality of service that is socially, environmentally, and economically sustainable. This book covers the most recent advances in IoT, it discusses Smart City implementation, and offers both quantitative and qualitative research.

It focuses on greening things such as green communication and networking, green design and implementations, green IoT services and applications, energy saving strategies, integrated RFIDs and sensor networks, mobility and network management, the cooperation of homogeneous and heterogeneous networks, smart objects, and green localization.

This book with its wide range of related topics in IoT and Smart City, will be useful for graduate students, researchers, academicians, institutions, and professionals that are interested in exploring the areas of IoT and Smart City.

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.

Today the healthcare sector is facing challenges such as detecting the cause of ailments, disease prevention, high operating costs, availability of skilled technicians and infrastructure bottlenecks. Intelligent healthcare management technologies are needed to manage these challenges. Healthcare organizations also need to continuously discover useful and actionable knowledge to gain insight from tons of data being generated for saving lives, reducing medical errors, enhancing efficiency, reducing costs and making the whole world a healthy place.

The book introduces techniques that developed using machine learning along with swarm intelligence in healthcare informatics. It also discusses one of the major applications of artificial intelligence: using machine learning to extract useful information from multimodal data optimally by using swarm intelligence. It reviews optimization methods that help to minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making. The objective of this book is to use swarm intelligence and machine learning techniques for various medical issues such as diagnosing cancer, brain tumor, diabetic retinopathy, heart diseases as well as drug design and development. The book will act as one-stop reference to think and explore swarm intelligence and machine learning algorithms seriously for real-time patient diagnosis.

Today the healthcare sector is facing challenges such as detecting the cause of ailments, disease prevention, high operating costs, availability of skilled technicians and infrastructure bottlenecks. Intelligent healthcare management technologies are needed to manage these challenges. Healthcare organizations also need to continuously discover useful and actionable knowledge to gain insight from tons of data being generated for saving lives, reducing medical errors, enhancing efficiency, reducing costs and making the whole world a healthy place.

The book introduces techniques that developed using machine learning along with swarm intelligence in healthcare informatics. It also discusses one of the major applications of artificial intelligence: using machine learning to extract useful information from multimodal data optimally by using swarm intelligence. It reviews optimization methods that help to minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making. The objective of this book is to use swarm intelligence and machine learning techniques for various medical issues such as diagnosing cancer, brain tumor, diabetic retinopathy, heart diseases as well as drug design and development. The book will act as one-stop reference to think and explore swarm intelligence and machine learning algorithms seriously for real-time patient diagnosis.

The increase in computing power and sensor data has driven Information Technology on end devices, such as smart phones or automobiles. The widespread application of IT across the globe includes manufacturing, engineering, retail, e-commerce, health care, education, financial services, banking, space exploration, politics (to help predict the sentiments of voter demographics), etc.

The papers in this conference proceeding examine and discuss various interdisciplinary researches that could accelerate the advent of Information Technology.

The increase in computing power and sensor data has driven Information Technology on end devices, such as smart phones or automobiles. The widespread application of IT across the globe includes manufacturing, engineering, retail, e-commerce, health care, education, financial services, banking, space exploration, politics (to help predict the sentiments of voter demographics), etc.

The papers in this conference proceeding examine and discuss various interdisciplinary researches that could accelerate the advent of Information Technology.