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This book gathers recent research in security and privacy to discuss, evaluate, and improve the novel approaches of data protection in IoT and edge and fog computing. The primary focus of the book addresses security mechanisms in IoT and edge/ fog computing, advanced secure deployments for large scaled edge/ fog computing, and new efficient data security strategy of IoT and edge/ fog computing. The book lays a foundation of the core concepts and principles of IoT and 5G security, walking the reader through the fundamental ideas. This book is aimed at researchers, graduate students, and engineers in the fields of secure IoT and edge/ fog computing. The book also presents selected papers from International Conference on Advanced Computing & Next-Generation Communication (ICACNGC 2022).
This book provides an overview of the next generation Internet of Things (IoT), ranging from research, innovation, development priorities, to enabling technologies in a global context. It is intended as a standalone in a series covering the activities of the Internet of Things European Research Cluster (IERC), including research, technological innovation, validation, and deployment. The text builds on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT-EPI), the IoT European Large-Scale Pilots Programme and the IoT European Security and Privacy Projects, presenting global views and state-of-the-art results regarding the next generation of IoT research, innovation, development, and deployment. The IoT and Industrial Internet of Things (IIoT) are evolving towards the next generation of Tactile IoT/IIoT, bringing together hyperconnectivity (5G and beyond), edge computing, Distributed Ledger Technologies (DLTs), virtual and augmented reality (VR/AR), and AI transformation. Following the wider adoption of consumer IoT, the next generation of IoT/IIoT innovation for business is driven by industries, addressing interoperability issues and providing new end-to-end security solutions to face continuous treats. The advances of AI technology in vision, speech recognition, natural language processing and dialog are enabling the development of end-to-end intelligent systems encapsulating multiple technologies, delivering services in real-time using limited resources. These developments are focusing on designing and delivering embedded and hierarchical AI solutions in IoT/IIoT, edge computing, using distributed architectures, DLTs platforms and distributed end-to-end security, which provide real-time decisions using less data and computational resources, while accessing each type of resource in a way that enhances the accuracy and performance of models in the various IoT/IIoT applications. The convergence and combination of IoT, AI and other related technologies to derive insights, decisions and revenue from sensor data provide new business models and sources of monetization. Meanwhile, scalable, IoT-enabled applications have become part of larger business objectives, enabling digital transformation with a focus on new services and applications. Serving the next generation of Tactile IoT/IIoT real-time use cases over 5G and Network Slicing technology is essential for consumer and industrial applications and support reducing operational costs, increasing efficiency and leveraging additional capabilities for real-time autonomous systems. New IoT distributed architectures, combined with system-level architectures for edge/fog computing, are evolving IoT platforms, including AI and DLTs, with embedded intelligence into the hyperconnectivity infrastructure. The next generation of IoT/IIoT technologies are highly transformational, enabling innovation at scale, and autonomous decision-making in various application domains such as healthcare, smart homes, smart buildings, smart cities, energy, agriculture, transportation and autonomous vehicles, the military, logistics and supply chain, retail and wholesale, manufacturing, mining and oil and gas.
Edge computational intelligence is an interface between edge computing and artificial intelligence (AI) technologies. This interfacing represents a paradigm shift in the world of work by enabling a broad application areas and customer-friendly solutions. Edge computational intelligence technologies are just in their infancy. Edge Computational Intelligence for AI-Enabled IoT Systems looks at the trends and advances in edge computing and edge AI, the services rendered by them, related security and privacy issues, training algorithms, architectures, and sustainable AI-enabled IoT systems. Together, these technologies benefit from ultra-low latency, faster response times, lower bandwidth costs and resilience from network failure, and the book explains the advantages of systems and applications using intelligent IoT devices that are at the edge of a network and close to users. It explains how to make most of edge and cloud computing as complementary technologies or used in isolation for extensive and widespread applications. The advancement in IoT devices, networking facilities, parallel computation and 5G, and robust infrastructure for generalized machine learning have made it possible to employ edge computational intelligence in diverse areas and in diverse ways. The book begins with chapters that cover Edge AI services on offer as compared to conventional systems. These are followed by chapters that discuss security and privacy issues encountered during the implementation and execution of edge AI and computing services The book concludes with chapters looking at applications spread across different areas of edge AI and edge computing and also at the role of computational intelligence in AI-driven IoT systems.
This book aims to provide the latest research developments and results in the domain of AI techniques for smart cyber ecosystems. It presents a holistic insight into AI-enabled theoretic approaches and methodology in IoT networking, security analytics using AI tools and network automation, which ultimately enable intelligent cyber space. This book will be a valuable resource for students, researchers, engineers and policy makers working in various areas related to cybersecurity and privacy for Smart Cities. This book includes chapters titled "An Overview of the Artificial Intelligence Evolution and Its Fundamental Concepts, and Their Relationship with IoT Security", "Smart City: Evolution and Fundamental Concepts", "Advances in AI-Based Security for Internet of Things in Wireless Virtualization Environment", "A Conceptual Model for Optimal Resource Sharing of Networked Microgrids Focusing Uncertainty: Paving Path to Eco-friendly Smart Cities", "A Novel Framework for a Cyber Secure Smart City", "Contemplating Security Challenges and Threats for Smart Cities", "Self-Monitoring Obfuscated IoT Network", "Introduction to Side Channel Attacks and Investigation of Power Analysis and Fault Injection Attack Techniques", "Collaborative Digital Forensic Investigations Model for Law Enforcement: Oman as a Case Study", "Understanding Security Requirements and Challenges in the Industrial Internet of Things: A Review", "5G Security and the Internet of Things", "The Problem of Deepfake Videos and How to Counteract Them in Smart Cities", "The Rise of Ransomware Aided by Vulnerable IoT Devices", "Security Issues in Self-Driving Cars within Smart Cities", and "Trust-Aware Crowd Associated Network-Based Approach for Optimal Waste Management in Smart Cities". This book provides state-of-the-art research results and discusses current issues, challenges, solutions and recent trends related to security and organization within IoT and Smart Cities. We expect this book to be of significant importance not only to researchers and practitioners in academia, government agencies and industries, but also for policy makers and system managers. We anticipate this book to be a valuable resource for all those working in this new and exciting area, and a "must have" for all university libraries.
The industrial landscape is changing rapidly, and so is global society. This change is driven by the growing adoption of the Industrial Internet of Things (IIoT) and artificial intelligence (AI) technologies. IIoT and AI are transforming the way industrial engineering is done, enabling new levels of automation, productivity, and efficiency. However, as IIoT and AI become more pervasive in the industrial world, they also offer new security risks that must be addressed to ensure the reliability and safety of critical systems. Industrial Internet of Things Security: Protecting AI-Enabled Engineering Systems in Cloud and Edge Environments provides a comprehensive guide to IIoT security, covering topics such as network architecture, risk management, data security, and compliance. It addresses the unique security challenges that the cloud and edge environments pose, providing practical guidance for securing IIoT networks in these contexts. It includes numerous real-world case studies and examples, providing readers with practical insights into how IIoT security and AI-enabled industrial engineering are being implemented in various industries. Best practices are emphasized for the readers to ensure the reliability, safety, and security of their systems while also learning the latest developments in IIoT security for AI-enabled industrial engineering systems in this rapidly evolving field. By offering step-by-step guidance for the implantation process along with best practices, this book becomes a valuable resource for practitioners and engineers in the areas of industrial engineering, IT, computer engineering, and anyone looking to secure their IIoT network against cyber threats.
The book provides an examination of how fog security is changing the information technology industry and will continue to in the next decade. The authors first discuss how fog enables key applications in wireless 5G, the Internet of Things, and big data. The book then presents an overview of fog/edge computing, focusing on its relationship with cloud technology, Internet of Things and the future with the use of secure 5G/6G communication. The book also presents a comprehensive overview of liabilities in fog/edge computing within multi-level architectures and the intelligent management. The last part of the book reviews applications of fog/edge computing in smart cities, including in Industrial IoT, edge-based augmented reality, data streaming, and blockchain-based.
"Integration of Fog computing with the resource limited IoT network, formulate the concept of Fog-enabled IoT system. Due to large number of deployments of IoT devices, a IoT is a main source of Big data and a very high volume of sensing data is generated by IoT system such as smart cities and smart grid applications. To provide a fast and efficient data analytics solution for Fog-enabled IoT system is a very fundamental research issue. This book focus on Big data Analytics in Fog-enabled-IoT system and provides a comprehensive collection of chapters that are touches different issues related to Healthcare system, Cyber threat detection, Malware detection, security and privacy of big IoT data and IoT network. This book emphasizes and facilitate a greater understanding of various security and privacy approaches using the advance AI and Big data technologies like machine/deep learning, federated learning, blockchain, edge computing and the countermeasures to overcome the vulnerabilities of the Fog-enabled IoT system"--
Over the past few years, the demand for data traffic has experienced explosive growth thanks to the increasing need to stay online. New applications of communications, such as wearable devices, autonomous systems, drones, and the Internet of Things (IoT), continue to emerge and generate even more data traffic with vastly different performance requirements. With the COVID-19 pandemic, the need to stay online has become even more crucial, as most of the fields, would they be industrial, educational, economic, or service-oriented, had to go online as best as they can. As the data traffic is expected to continuously strain the capacity of future communication networks, these networks need to evolve consistently in order to keep up with the growth of data traffic. Thus, more intelligent processing, operation, and optimization will be needed for tomorrow’s communication networks. The Sixth Generation (6G) technology is latest approach for mobile systems or edge devices in terms of reduce traffic congestions, energy consumption blending with IoT devices applications. The 6G network works beyond the 5G (B5G), where we can use various platforms as an application e.g. fog computing enabled IoT networks, Intelligent techniques for SDN network, 6G enabled healthcare industry, energy aware location management. Still this technology must resolve few challenges like security, IoT enabled trust network. This book will focus on the use of AI/ML-based techniques to solve issues related to 6G enabled networks, their layers, as well as their applications. It will be a collection of original contributions regarding state-of-the-art AI/ML-based solutions for signal detection, channel modeling, resource optimization, routing protocol design, transport layer optimization, user/application behavior prediction 6G enabled software-defined networking, congestion control, communication network optimization, security, and anomaly detection. The proposed edited book emphasis on the 6G network blended with Fog-IoT networks to introduce its applications and future perspectives that helps the researcher to apply this technique in their domain and it may also helpful to resolve the challenges and future opportunities with 6G networks.