Mariya Ouaissa – författare

This book is a reference on digital technology and its impact on sustainability, providing insight into sustainable practices globally. It focuses on the critical practices leading to sustainable initiatives among various organizations, IT infrastructure, communities, and government compliance. The book describes the green computing paradigms and the impact of a circular economy with a focus on sustainable practices in a post-pandemic world.Sustainable Digital Technologies: Trends, Impacts, and Assessments discusses the critical factors leading to sustainable initiatives in a global economy. It highlights the impact of digital technology and Industry 4.0 in today’s world. The book focuses on the role, responsibility, and the effect of the Internet of Things for digital sustainability and practices. It describes implementation strategies for green cloud computing and presents additional strategies for sustainable practices in a post-pandemic world.This publication is designed for use by technology development academicians, data scientists, industrial professionals, researchers, and students interested in uncovering the latest innovations in the field and the current research on problem-oriented processing techniques in sustainable and evolutionary computing applications with reduced energy channelization.

This book is a reference on digital technology and its impact on sustainability, providing insight into sustainable practices globally. It focuses on the critical practices leading to sustainable initiatives among various organizations, IT infrastructure, communities, and government compliance. The book describes the green computing paradigms and the impact of a circular economy with a focus on sustainable practices in a post-pandemic world.Sustainable Digital Technologies: Trends, Impacts, and Assessments discusses the critical factors leading to sustainable initiatives in a global economy. It highlights the impact of digital technology and Industry 4.0 in today’s world. The book focuses on the role, responsibility, and the effect of the Internet of Things for digital sustainability and practices. It describes implementation strategies for green cloud computing and presents additional strategies for sustainable practices in a post-pandemic world.This publication is designed for use by technology development academicians, data scientists, industrial professionals, researchers, and students interested in uncovering the latest innovations in the field and the current research on problem-oriented processing techniques in sustainable and evolutionary computing applications with reduced energy channelization.

The book showcases how advanced cybersecurity and forensic techniques can be applied to various computational issues. It further covers the advanced exploitation tools that are used in the domain of ethical hacking and penetration testing.• Focuses on tools used in performing mobile and SIM forensics, static and dynamic memory analysis, and deep web forensics• Covers advanced tools in the domain of data hiding and steganalysis• Discusses the role and application of artificial intelligence and big data in cybersecurity• Elaborates on the use of advanced cybersecurity and forensics techniques in computational issues• Includes numerous open-source tools such as NMAP, Autopsy, and Wireshark used in the domain of digital forensicsThe text is primarily written for senior undergraduates, graduate students, and academicresearchers, in the fields of computer science, electrical engineering, cybersecurity,and forensics.

The book showcases how advanced cybersecurity and forensic techniques can be applied to various computational issues. It further covers the advanced exploitation tools that are used in the domain of ethical hacking and penetration testing.• Focuses on tools used in performing mobile and SIM forensics, static and dynamic memory analysis, and deep web forensics• Covers advanced tools in the domain of data hiding and steganalysis• Discusses the role and application of artificial intelligence and big data in cybersecurity• Elaborates on the use of advanced cybersecurity and forensics techniques in computational issues• Includes numerous open-source tools such as NMAP, Autopsy, and Wireshark used in the domain of digital forensicsThe text is primarily written for senior undergraduates, graduate students, and academicresearchers, in the fields of computer science, electrical engineering, cybersecurity,and forensics.

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 FEATURESHighlights innovative principles and practices using next generation computing technologies based cybersecurityPresents an introduction to recent trends regarding the convergence of AI/ML in cybersecurityOffers an overview of theoretical, practical, simulation concepts of cybersecurity

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 FEATURESHighlights innovative principles and practices using next generation computing technologies based cybersecurityPresents an introduction to recent trends regarding the convergence of AI/ML in cybersecurityOffers an overview of theoretical, practical, simulation concepts of cybersecurity

This book presents a comprehensive exploration of LPWANs, delving into their fundamental concepts, underlying technologies, and the multifaceted challenges they tackle. This book recognizes that LPWANs don't operate in isolation; they are intimately intertwined with Artificial Intelligence and Machine Learning (AI/ML) technologies, which play a pivotal role in optimizing LPWAN performance and capabilities. The book is a collection of original contributions regarding air interface, transmission technologies and novel network architectures, such as network slicing, cloud/fog/edge computing, ad hoc networks and software-defined network. Also, this book provides a guide for researchers of IoT applications to choose suitable LPWAN technologies and describe the design aspects, network architectures, security issues and challenges.Features:Explains machine learning algorithms onto low-power wide area network sensors for compressed communications. Illustrates wireless-based Internet of Things networks using low-power wide area networks technology for quality air. Presents cognitive Internet of Things networks using wireless communication, and low-power wide area network technologies for Ad Hoc networks. Discusses a comprehensive study of low-power wide area networks for flying Ad Hoc networks. Showcases the study of energy efficient techniques aided by low-power wide area network technologies for the Internet of Things networks. The text is aimed at senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.

The aim of this book is to highlight the most promising lines of research, using new enabling technologies and methods based on AI/ML techniques to solve issues and challenges related to intelligent and computing systems. Intelligent computing easily collects data using smart technological applications like IoT-based wireless networks, digital healthcare, transportation, blockchain, 5.0 industry and deep learning for better decision making. AI enabled networks will be integrated in smart cities' concept for interconnectivity. Wireless networks will play an important role. The digital era of computational intelligence will change the dynamics and lifestyle of human beings. Future networks will be introduced with the help of AI technology to implement cognition in real-world applications. Cyber threats are dangerous to encode information from network. Therefore, AI-Intrusion detection systems need to be designed for identification of unwanted data traffic.This book:Provides a better understanding of artificial intelligence-based applications for future smart citiesPresents a detailed understanding of artificial intelligence tools for intelligent technologiesShowcases intelligent computing technologies in obtaining optimal solutions using artificial intelligenceDiscusses energy-efficient routing protocols using artificial intelligence for Flying ad-hoc networks (FANETs)Covers machine learning-based Intrusion detection system (IDS) for smart gridIt is primarily written for senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, and computer engineering.

This book addresses and disseminates state-of-the-art research and development in the applications of soft computing techniques for renewable energy systems. It covers topics such as solar energy, wind energy, and solar concentrator technologies, as well as building systems and power generation systems. In all these areas, applications of soft computing methods such as artificial neural networks, genetic algorithms, particle swarm optimization, cuckoo search, fuzzy logic, and a combination of these, called hybrid systems, are included. This book is a source for students interested in the fields of renewable energy and the application of the soft computing. In addition, our book can be considered as a reference for researchers and academics since it will include applications of soft computing in different renewable energy systems.

This book addresses and disseminates state-of-the-art research and development in the applications of soft computing techniques for renewable energy systems. It covers topics such as solar energy, wind energy, and solar concentrator technologies, as well as building systems and power generation systems. In all these areas, applications of soft computing methods such as artificial neural networks, genetic algorithms, particle swarm optimization, cuckoo search, fuzzy logic, and a combination of these, called hybrid systems, are included. This book is a source for students interested in the fields of renewable energy and the application of the soft computing. In addition, our book can be considered as a reference for researchers and academics since it will include applications of soft computing in different renewable energy systems.

This book focuses on the techniques of artificial intelligence that are mainly used in the power electronics field for the optimization of lost vehicle power. With the intention of optimizing the powerful energy of the vehicles and producing reliable energy, the most efficient methods, algorithms, and strategies of ethical artificial intelligence (AI) are being applied. By employing machine learning methods, the optimization of power energy in vehicles can be quickly recovered and managed efficiently. In today’s bustling world, power energy is indispensable for progress, yet in congested Vehicular Ad-hoc Networks (VANETs), vehicles often face power depletion and decreased efficiency. This book explores these challenges, encompassing not only power but also other critical power electronics within vehicles. We aim to introduce innovative approaches, leveraging ethical AI methods, to optimize energy performance in the face of these difficulties. Through this exploration, we seek to provide practical insights into navigating congested VANET environments while upholding ethical principles in technological advancements. Our book will discuss the current power energy concerns faced by vehicles and also contribute a novel strategy to overcome those concerns. The employment of ethical AI in vehicular power energy will undoubtedly improve the effectiveness and production of vehicles.

Future Communication Systems Using Artificial Intelligence, Internet of Things and Data Science mainly focuses on the techniques of artificial intelligence (AI), Internet of Things (IoT) and data science for future communications systems.The goal of AI, IoT and data science for future communications systems is to create a venue for industry and academics to collaborate on the development of network and system solutions based on data science, AI and IoT. Recent breakthroughs in IoT, mobile and fixed communications and computation have paved the way for a data‑centric society of the future. New applications are increasingly reliant on machine‑to‑machine connections, resulting in unusual workloads and the need for more efficient and dependable infrastructures. Such a wide range of traffic workloads and applications will necessitate dynamic and highly adaptive network environments capable of self‑optimization for the task at hand while ensuring high dependability and ultra‑low latency.Networking devices, sensors, agents, meters and smart vehicles/systems generate massive amounts of data, necessitating new levels of security, performance and dependability. Such complications necessitate the development of new tools and approaches for providing successful services, management and operation. Predictive network analytics will play a critical role in insight generation, process automation required for adapting and scaling to new demands, resolving issues before they impact operational performance (e.g., preventing network failures and anticipating capacity requirements) and overall network decision‑making. To increase user experience and service quality, data mining and analytic techniques for inferring quality of experience (QoE) signals are required.AI, IoT, machine learning, reinforcement learning and network data analytics innovations open new possibilities in areas such as channel modeling and estimation, cognitive communications, interference alignment, mobility management, resource allocation, network control and management, network tomography, multi‑agent systems and network ultra‑broadband deployment prioritization. These new analytic platforms will aid in the transformation of our networks and user experience. Future networks will enable unparalleled automation and optimization by intelligently gathering, analyzing, learning and controlling huge volumes of information.

Cognitive Machine Intelligence: Applications, Challenges, and Related Technologies offers a compelling exploration of the transformative landscape shaped by the convergence of machine intelligence, artificial intelligence, and cognitive computing. In this book, the authors navigate through the intricate realms of technology, unveiling the profound impact of cognitive machine intelligence on diverse fields such as communication, healthcare, cybersecurity, and smart city development. The chapters present study on robots and drones to the integration of machine learning with wireless communication networks, IoT, quantum computing, and beyond. The book explores the essential role of machine learning in healthcare, security, and manufacturing. With a keen focus on privacy, trust, and the improvement of human lifestyles, this book stands as a comprehensive guide to the novel techniques and applications driving the evolution of cognitive machine intelligence. The vision presented here extends to smart cities, where AI-enabled techniques contribute to optimal decision-making, and future computing systems address end-to-end delay issues with a central focus on Quality-of-Service metrics. Cognitive Machine Intelligence is an indispensable resource for researchers, practitioners, and enthusiasts seeking a deep understanding of the dynamic landscape at the intersection of artificial intelligence and cognitive computing.This book:Covers a comprehensive exploration of cognitive machine intelligence and its intersection with emerging technologies such as federated learning, blockchain, and 6G and beyond.Discusses the integration of machine learning with various technologies such as wireless communication networks, ad-hoc networks, software-defined networks, quantum computing, and big data.Examines the impact of machine learning on various fields such as healthcare, unmanned aerial vehicles, cybersecurity, and neural networks.Provides a detailed discussion on the challenges and solutions to future computer networks like end-to-end delay issues, Quality of Service (QoS) metrics, and security.Emphasizes the need to ensure privacy and trust while implementing the novel techniques of machine intelligence.It is primarily written for senior undergraduate and graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, and computer engineering.

Future Communication Systems Using Artificial Intelligence, Internet of Things and Data Science mainly focuses on the techniques of artificial intelligence (AI), Internet of Things (IoT) and data science for future communications systems.The goal of AI, IoT and data science for future communications systems is to create a venue for industry and academics to collaborate on the development of network and system solutions based on data science, AI and IoT. Recent breakthroughs in IoT, mobile and fixed communications and computation have paved the way for a data‑centric society of the future. New applications are increasingly reliant on machine‑to‑machine connections, resulting in unusual workloads and the need for more efficient and dependable infrastructures. Such a wide range of traffic workloads and applications will necessitate dynamic and highly adaptive network environments capable of self‑optimization for the task at hand while ensuring high dependability and ultra‑low latency.Networking devices, sensors, agents, meters and smart vehicles/systems generate massive amounts of data, necessitating new levels of security, performance and dependability. Such complications necessitate the development of new tools and approaches for providing successful services, management and operation. Predictive network analytics will play a critical role in insight generation, process automation required for adapting and scaling to new demands, resolving issues before they impact operational performance (e.g., preventing network failures and anticipating capacity requirements) and overall network decision‑making. To increase user experience and service quality, data mining and analytic techniques for inferring quality of experience (QoE) signals are required.AI, IoT, machine learning, reinforcement learning and network data analytics innovations open new possibilities in areas such as channel modeling and estimation, cognitive communications, interference alignment, mobility management, resource allocation, network control and management, network tomography, multi‑agent systems and network ultra‑broadband deployment prioritization. These new analytic platforms will aid in the transformation of our networks and user experience. Future networks will enable unparalleled automation and optimization by intelligently gathering, analyzing, learning and controlling huge volumes of information.

This book focuses on the techniques of artificial intelligence that are mainly used in the power electronics field for the optimization of lost vehicle power. With the intention of optimizing the powerful energy of the vehicles and producing reliable energy, the most efficient methods, algorithms, and strategies of ethical artificial intelligence (AI) are being applied. By employing machine learning methods, the optimization of power energy in vehicles can be quickly recovered and managed efficiently. In today’s bustling world, power energy is indispensable for progress, yet in congested Vehicular Ad-hoc Networks (VANETs), vehicles often face power depletion and decreased efficiency. This book explores these challenges, encompassing not only power but also other critical power electronics within vehicles. We aim to introduce innovative approaches, leveraging ethical AI methods, to optimize energy performance in the face of these difficulties. Through this exploration, we seek to provide practical insights into navigating congested VANET environments while upholding ethical principles in technological advancements. Our book will discuss the current power energy concerns faced by vehicles and also contribute a novel strategy to overcome those concerns. The employment of ethical AI in vehicular power energy will undoubtedly improve the effectiveness and production of vehicles.

Our book, Future of Tech Startups and Innovations in the Age of AI, mainly focuses on artificial intelligence (AI) tools, AI-based startups, AI-enabled innovations, Autonomous AI Agents (Auto-GPT), AI-based marketing startups, machine learning for organizations, AI-internet of things (IoT) for new tech companies, AI-enabled drones for agriculture industry, machine learning (ML)/deep learning (DL)-based drip farming, AI-based driverless cars, AI-based weather prediction startups, AI tools for personal branding, AI-based teaching, AI-based doctor/hospital startups, AI for game companies, AI-based finance tools, AI for human resource management, AI-powered management tools, AI tools for future pandemics, AI/ML-based transportation companies, AI for media, AI for carrier counseling, AI for customer care, AI for next generation businesses, and many more applications. AI tools and techniques will revolutionize startups all over the world. Entrepreneurs, engineers, and practitioners have already moved toward AI-based solutions to reshape businesses. AI/ML will create possibilities and opportunities for improving human lifestyles. AI-enabled startups will work on cost-effective solutions to solve difficult problems. Recently, many research companies are interested in providing solutions and investing a lot in AI-based startups. AI-driven products will revolutionize the "smart world." AI computing tech companies will help to model human speech recognition systems. Also, AI-based startups will focus on perception and reasoning of autonomous robotic systems. AI/ML-based tech startups will introduce smart online education systems for future pandemics. More interestingly, people are also moving for online job opportunities and trying to work from home. Future innovation needs closer relations between academia and industry. Therefore, online platforms need to be introduced that will only focus on academia and industry linkage. Future AI tech-based startups will focus more on research and development to introduce novel products to the market. Accordingly, engineers and many other people should be trained on AI tools and techniques to introduce innovative solutions for the smart world. In addition, integration of many new technologies with AI will be made possible. AI with IoT, smart cities, unmanned aerial vehicles (UAVs), wireless sensor networks, software-defined networks, network management, vehicular ad hoc networks, flying ad hoc networks, wireless communication technologies, ML, reinforcement learning, federated learning and other mechanisms will introduce new technological products.

Our book, Future of Tech Startups and Innovations in the Age of AI, mainly focuses on artificial intelligence (AI) tools, AI-based startups, AI-enabled innovations, Autonomous AI Agents (Auto-GPT), AI-based marketing startups, machine learning for organizations, AI-internet of things (IoT) for new tech companies, AI-enabled drones for agriculture industry, machine learning (ML)/deep learning (DL)-based drip farming, AI-based driverless cars, AI-based weather prediction startups, AI tools for personal branding, AI-based teaching, AI-based doctor/hospital startups, AI for game companies, AI-based finance tools, AI for human resource management, AI-powered management tools, AI tools for future pandemics, AI/ML-based transportation companies, AI for media, AI for carrier counseling, AI for customer care, AI for next generation businesses, and many more applications. AI tools and techniques will revolutionize startups all over the world. Entrepreneurs, engineers, and practitioners have already moved toward AI-based solutions to reshape businesses. AI/ML will create possibilities and opportunities for improving human lifestyles. AI-enabled startups will work on cost-effective solutions to solve difficult problems. Recently, many research companies are interested in providing solutions and investing a lot in AI-based startups. AI-driven products will revolutionize the "smart world." AI computing tech companies will help to model human speech recognition systems. Also, AI-based startups will focus on perception and reasoning of autonomous robotic systems. AI/ML-based tech startups will introduce smart online education systems for future pandemics. More interestingly, people are also moving for online job opportunities and trying to work from home. Future innovation needs closer relations between academia and industry. Therefore, online platforms need to be introduced that will only focus on academia and industry linkage. Future AI tech-based startups will focus more on research and development to introduce novel products to the market. Accordingly, engineers and many other people should be trained on AI tools and techniques to introduce innovative solutions for the smart world. In addition, integration of many new technologies with AI will be made possible. AI with IoT, smart cities, unmanned aerial vehicles (UAVs), wireless sensor networks, software-defined networks, network management, vehicular ad hoc networks, flying ad hoc networks, wireless communication technologies, ML, reinforcement learning, federated learning and other mechanisms will introduce new technological products.

This book presents a comprehensive exploration of LPWANs, delving into their fundamental concepts, underlying technologies, and the multifaceted challenges they tackle. This book recognizes that LPWANs don't operate in isolation; they are intimately intertwined with Artificial Intelligence and Machine Learning (AI/ML) technologies, which play a pivotal role in optimizing LPWAN performance and capabilities. The book is a collection of original contributions regarding air interface, transmission technologies and novel network architectures, such as network slicing, cloud/fog/edge computing, ad hoc networks and software-defined network. Also, this book provides a guide for researchers of IoT applications to choose suitable LPWAN technologies and describe the design aspects, network architectures, security issues and challenges.Features:Explains machine learning algorithms onto low-power wide area network sensors for compressed communications. Illustrates wireless-based Internet of Things networks using low-power wide area networks technology for quality air. Presents cognitive Internet of Things networks using wireless communication, and low-power wide area network technologies for Ad Hoc networks. Discusses a comprehensive study of low-power wide area networks for flying Ad Hoc networks. Showcases the study of energy efficient techniques aided by low-power wide area network technologies for the Internet of Things networks. The text is aimed at senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.

The objective of this book is to showcase recent solutions and discuss the opportunities that AI, blockchain, and even their combinations can present to solve the issue of Internet of Things (IoT) security. It delves into cuttingedge technologies and methodologies, illustrating how these innovations can fortify IoT ecosystems against security threats. The discussion includes a comprehensive analysis of AI techniques such as machine learning and deep learning, which can detect and respond to security breaches in real time. The role of blockchain in ensuring data integrity, transparency, and tamper- proof transactions is also thoroughly examined. Furthermore, this book will present solutions that will help analyze complex patterns in user data and ultimately improve productivity.

The aim of this book is to highlight the most promising lines of research, using new enabling technologies and methods based on AI/ML techniques to solve issues and challenges related to intelligent and computing systems. Intelligent computing easily collects data using smart technological applications like IoT-based wireless networks, digital healthcare, transportation, blockchain, 5.0 industry and deep learning for better decision making. AI enabled networks will be integrated in smart cities' concept for interconnectivity. Wireless networks will play an important role. The digital era of computational intelligence will change the dynamics and lifestyle of human beings. Future networks will be introduced with the help of AI technology to implement cognition in real-world applications. Cyber threats are dangerous to encode information from network. Therefore, AI-Intrusion detection systems need to be designed for identification of unwanted data traffic.This book:Provides a better understanding of artificial intelligence-based applications for future smart citiesPresents a detailed understanding of artificial intelligence tools for intelligent technologiesShowcases intelligent computing technologies in obtaining optimal solutions using artificial intelligenceDiscusses energy-efficient routing protocols using artificial intelligence for Flying ad-hoc networks (FANETs)Covers machine learning-based Intrusion detection system (IDS) for smart gridIt is primarily written for senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, and computer engineering.

The objective of this book is to showcase recent solutions and discuss the opportunities that AI, blockchain, and even their combinations can present to solve the issue of Internet of Things (IoT) security. It delves into cuttingedge technologies and methodologies, illustrating how these innovations can fortify IoT ecosystems against security threats. The discussion includes a comprehensive analysis of AI techniques such as machine learning and deep learning, which can detect and respond to security breaches in real time. The role of blockchain in ensuring data integrity, transparency, and tamper- proof transactions is also thoroughly examined. Furthermore, this book will present solutions that will help analyze complex patterns in user data and ultimately improve productivity.

Cognitive Machine Intelligence: Applications, Challenges, and Related Technologies offers a compelling exploration of the transformative landscape shaped by the convergence of machine intelligence, artificial intelligence, and cognitive computing. In this book, the authors navigate through the intricate realms of technology, unveiling the profound impact of cognitive machine intelligence on diverse fields such as communication, healthcare, cybersecurity, and smart city development. The chapters present study on robots and drones to the integration of machine learning with wireless communication networks, IoT, quantum computing, and beyond. The book explores the essential role of machine learning in healthcare, security, and manufacturing. With a keen focus on privacy, trust, and the improvement of human lifestyles, this book stands as a comprehensive guide to the novel techniques and applications driving the evolution of cognitive machine intelligence. The vision presented here extends to smart cities, where AI-enabled techniques contribute to optimal decision-making, and future computing systems address end-to-end delay issues with a central focus on Quality-of-Service metrics. Cognitive Machine Intelligence is an indispensable resource for researchers, practitioners, and enthusiasts seeking a deep understanding of the dynamic landscape at the intersection of artificial intelligence and cognitive computing.This book:Covers a comprehensive exploration of cognitive machine intelligence and its intersection with emerging technologies such as federated learning, blockchain, and 6G and beyond.Discusses the integration of machine learning with various technologies such as wireless communication networks, ad-hoc networks, software-defined networks, quantum computing, and big data.Examines the impact of machine learning on various fields such as healthcare, unmanned aerial vehicles, cybersecurity, and neural networks.Provides a detailed discussion on the challenges and solutions to future computer networks like end-to-end delay issues, Quality of Service (QoS) metrics, and security.Emphasizes the need to ensure privacy and trust while implementing the novel techniques of machine intelligence.It is primarily written for senior undergraduate and graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, and computer engineering.

The aim of this book is to explore the definitions and fundamentals of offensive security versus defensive security and describe the different tools and technologies for protecting against cyber threats. The book offers strategies of practical aspects of cybersecurity, covers the main disciplines needed to understand cybersecurity, and demonstrates ethical and legal concepts of cyber activities. It presents important concepts relevant for cybersecurity strategies, including the concept of cybercrime, cyber defense, protection of IT systems, and analysis of risks.

The aim of this book is to explore the definitions and fundamentals of offensive security versus defensive security and describe the different tools and technologies for protecting against cyber threats. The book offers strategies of practical aspects of cybersecurity, covers the main disciplines needed to understand cybersecurity, and demonstrates ethical and legal concepts of cyber activities. It presents important concepts relevant for cybersecurity strategies, including the concept of cybercrime, cyber defense, protection of IT systems, and analysis of risks.

Machine Learning for Radio Resource Management and Optimization in 5G and Beyond highlights a new line of research that uses innovative technologies and methods based on artificial intelligence/machine learning techniques to address issues and challenges related to radio resource management in 5G and 6G communication systems. This book provides comprehensive coverage of current and emerging waveform design, channel modeling, multiple access, random access, scheduling, network slicing, and resource optimization for 5G wireless networks and beyond.This book is suitable for researchers, scholars, and industry professionals working in different fields related to mobile networks and intelligent systems. Additionally, it serves as a hands‑on resource for students interested in the fields of cellular networks (5G/6G) and computational intelligence.

Machine Learning for Radio Resource Management and Optimization in 5G and Beyond highlights a new line of research that uses innovative technologies and methods based on artificial intelligence/machine learning techniques to address issues and challenges related to radio resource management in 5G and 6G communication systems. This book provides comprehensive coverage of current and emerging waveform design, channel modeling, multiple access, random access, scheduling, network slicing, and resource optimization for 5G wireless networks and beyond.This book is suitable for researchers, scholars, and industry professionals working in different fields related to mobile networks and intelligent systems. Additionally, it serves as a hands‑on resource for students interested in the fields of cellular networks (5G/6G) and computational intelligence.

This book is aimed at a diverse audience including students, researchers, academicians, cybersecurity professionals, IT managers, Metaverse developers, business leaders, policymakers, and tech enthusiasts. This book is for everyone—from beginners to experts, researchers, and students. It offers insights and tools suitable for people with different levels of knowledge, making it accessible to a wide range of readers. The book fits alongside other published books by addressing the rapidly evolving intersection of cybersecurity and the Metaverse, a niche yet increasingly critical area.Unlike traditional cybersecurity books that focus on current internet and IT infrastructures, this book uniquely targets the virtual environments of the Metaverse. It combines advanced technological insights with practical strategies, providing a specialized resource that bridges the gap between conventional cybersecurity literature and the futuristic needs of Metaverse security. This positions it as an essential read for those looking to stay ahead in the field of cybersecurity within the context of next-generation internet platforms.

This book explores the integration of Artificial Intelligence (AI) with the Internet of Things (IoT) to address security challenges in smart environments. It delves into how AI enhances the governance of information security by automating processes, detecting threats, and ensuring the protection of data in interconnected IoT systems. It covers theoretical foundations, practical frameworks, and case studies, offering insights into securing smart cities, homes, industries, and healthcare systems. It also emphasizes governance models that leverage AI to manage security policies and risk in dynamic, data-driven ecosystems.This title focuses on the study and application of AI of Things in the field of information security governance. Intelligent environments, characterized by increasing connectivity of devices and systems, present unique challenges for information security. The use of AI of Things offers opportunities to enhance security in these complex environments.

This book delves into the revolutionary ways in which AI-driven innovations are enhancing every aspect of cybersecurity, from threat detection and response automation to risk management and endpoint protection. As AI continues to evolve, the synergy between cybersecurity and artificial intelligence promises to reshape the landscape of digital defence, providing the tools needed to tackle complex, ever-evolving cyber threats. Designed for professionals, researchers, and decision-makers, this book emphasizes that understanding and leveraging AI in cybersecurity is not just advantageous—it is essential for building robust, future-proof defences in a world where digital security is paramount.