The Internet of Things (IoT) involves physical devices, cars, household appliances, and any other physical appliance equipped with sensors, software, and network connections to gather and communicate data. Nowadays, this technology is embedded in everything from simple smart devices, to wearable equipment, to complex industrial machinery and transportation infrastructures. On the other hand, IoT equipment has been designed without considering security issues. Consequently, there are many challenges in terms of protection against IoT threats, which can lead to distressing situations. In fact, unlike other technological solutions, there are few standards and guidelines governing the protection of IoT technology. Moreover, few users are aware of the risks associated with IoT systems. Hence, Blockchain and Machine Learning for IoT Security discusses various recent techniques and solutions related to IoT deployment, especially security and privacy. This book addresses a variety of subjects, including a comprehensive overview of the IoT, and covers in detail the security challenges at each layer by considering how both the architecture and underlying technologies are employed. As acknowledged experts in the field, the authors provide remediation solutions for impaired security, as well as mitigation methods, and offer both prevention and improvement suggestions. Key Features: Offers a unique perspective on IoT security by introducing Machine Learning and Blockchain solutions Presents a well-rounded overview of the most recent advances in IoT security and privacy Discusses practical solutions and real-world cases for IoT solutions in various areas Provides solutions for securing IoT against various threats Discuses Blockchain technology as a solution for IoT This book is designed to provide all the necessary knowledge for young researchers, academics, and industry professionals who want to understand the advantages of artificial intelligence technology, machine learning, data analysis methodology, and Blockchain for securing IoT technologies.

MACHINE LEARNING APPROACHES FOR CONVERGENCE OF IOT AND BLOCKCHAIN The unique aspect of this book is that its focus is the convergence of machine learning, IoT, and blockchain in a single publication. Blockchain technology and the Internet of Things (IoT) are two of the most impactful trends to have emerged in the field of machine learning. Although there are a number of books available solely on the subjects of machine learning, IoT and blockchain technology, no such book has been available which focuses on machine learning techniques for IoT and blockchain convergence until now. Thus, this book is unique in terms of the topics it covers. Designed as an essential guide for all academicians, researchers, and those in industry who are working in related fields, this book will provide insights into the convergence of blockchain technology and the IoT with machine learning. Highlights of the book include: Examines many industries such as agriculture, manufacturing, food production, healthcare, the military, and IT Security of the Internet of Things using blockchain and AI Developing smart cities and transportation systems using machine learning and IoT Audience The target audience of this book is professionals and researchers (artificial intelligence specialists, systems engineers, information technologists) in the fields of machine learning, IoT, and blockchain technology.

The Industry 4.0 revolution is changing the world around us. Artificial intelligence and machine learning, automation and robotics, big data, Internet of Things, augmented reality, virtual reality, and creativity are the tools of Industry 4.0. Improved collaboration is seen between smart systems and humans, which merges humans' critical and cognitive thinking abilities with highly accurate and fast industrial automation. Securing IoT in Industry 4.0 Applications with Blockchain examines the role of IoT in Industry 4.0 and how it can be made secure through various technologies including blockchain. The book begins with an in-depth look at IoT and discusses applications, architecture, technologies, tools, and programming languages. It then examines blockchain and cybersecurity, as well as how blockchain achieves cybersecurity. It also looks at cybercrimes and their preventive measures and issues related to IoT security and trust. Features An overview of how IoT is used to improve the performance of Industry 4.0 systems The evolution of the Industrial Internet of Things (IIoT), its proliferation and market share, and some examples across major industries An exploration of how smart farming is helping farmers prevent plant disease The concepts behind the Internet of Nano Things (IoNT), including the nanomachine and nanonetwork architecture and nano-communication paradigms A look at how blockchains can enhance cybersecurity in a variety of applications, including smart contracts, transferring financial instruments, and Public Key Infrastructure An overview of the structure and working of a blockchain, including the types, evolution, benefits, and applications of blockchain to industries A framework of technologies designed to shield networks, computers, and data from malware, vulnerabilities, and unauthorized activities An explanation of the automation system employed in industries along with its classification, functionality, flexibility, limitations, and applications

MACHINE LEARNING APPROACHES FOR CONVERGENCE OF IOT AND BLOCKCHAIN The unique aspect of this book is that its focus is the convergence of machine learning, IoT, and blockchain in a single publication. Blockchain technology and the Internet of Things (IoT) are two of the most impactful trends to have emerged in the field of machine learning. Although there are a number of books available solely on the subjects of machine learning, IoT and blockchain technology, no such book has been available which focuses on machine learning techniques for IoT and blockchain convergence until now. Thus, this book is unique in terms of the topics it covers. Designed as an essential guide for all academicians, researchers, and those in industry who are working in related fields, this book will provide insights into the convergence of blockchain technology and the IoT with machine learning. Highlights of the book include: Examines many industries such as agriculture, manufacturing, food production, healthcare, the military, and IT Security of the Internet of Things using blockchain and AI Developing smart cities and transportation systems using machine learning and IoT Audience The target audience of this book is professionals and researchers (artificial intelligence specialists, systems engineers, information technologists) in the fields of machine learning, IoT, and blockchain technology.

Integration of IoT (Internet of Things) with big data and cloud computing has brought forward numerous advantages and challenges such as data analytics, integration, and storage. This book highlights these challenges and provides an integrating framework for these technologies, illustrating the role of blockchain in all possible facets of IoT security. Furthermore, it investigates the security and privacy issues associated with various IoT systems along with exploring various machine learning-based IoT security solutions. This book brings together state-of-the-art innovations, research activities (both in academia and in industry), and the corresponding standardization impacts of 5G as well. Aimed at graduate students, researchers in computer science and engineering, communication networking, IoT, machine learning and pattern recognition, this book Showcases the basics of both IoT and various security paradigms supporting IoT, including Blockchain Explores various machine learning-based IoT security solutions and highlights the importance of IoT for industries and smart cities Presents various competitive technologies of Blockchain, especially concerned with IoT security Provides insights into the taxonomy of challenges, issues, and research directions in IoT-based applications Includes examples and illustrations to effectively demonstrate the principles, algorithm, applications, and practices of security in the IoT environment

The purpose of this edited book is to present and showcase the basic fundamentals, applications, and integration of both IoT and Blockchain. The trend of applying Blockchain to IoT is rapidly growing because it helps to overcome various challenges faced by IoT, from smart manufacturing to unmanned aerial vehicles. Thise book aims to showcase the basics of both IoT and Blockchain as well as the integration and challenges for existing practitioners. Thise book initiates conversations among technologists, engineers, scientists, and clinicians to synergize their efforts in producing low-cost, high-performance, highly efficient, deployable IoT systems. Thise book is theory-based and is useful for engineers from various disciplines, including industrial engineering, computer science, electronics, telecommunications, electrical, agricultural, and cybersecurity, along with researchers, professionals, and students.

Machine Learning, Cyber Security, and Blockchain in Smart Environment: Application and Challenges provides far-reaching insights into the recent techniques forming the backbone of smart environments, and addresses the vulnerabilities that give rise to the challenges in real-word implementation. The book focuses on the benefits related to the emerging applications such as machine learning, blockchain and cyber security. Key Features: Introduces the latest trends in the fields of machine learning, blockchain and cyber security Discusses the fundamentals, challenges and architectural overviews with concepts Explores recent advancements in machine learning, blockchain, and cyber security Examines recent trends in emerging technologies This book is primarily aimed at graduates, researchers, and professionals working in the areas of machine learning, blockchain, and cyber security.

By 2020, experts forecast that up to 28 billion devices will be connected to the Internet, with only one third of them being computers, smartphones, smartwatches, and tablets. The remaining two thirds will be other “devices” – sensors, terminals, household appliances, thermostats, televisions, automobiles, production machinery, urban infrastructure and many other “things”, which traditionally have not been Internet enabled.This “Internet of Things” (IoT) represents a remarkable transformation of the way in which our world will soon interact. Much like the World Wide Web connected computers to networks, and the next evolution mobile devices connected people to the Internet and other people, IoT looks poised to interconnect devices, people, environments, virtual objects and machines in ways that only science fiction writers could have imagined. In a nutshell the Internet of Things (IoT) is the convergence of connecting people, things, data and processes; it is transforming our life, business and everything in between. Secure and Smart IoT explores many aspects of the Internet of Things and explains many of the complicated principles of IoT and the new advancements in IoT including using Fog Computing, AI and Blockchain technology.

This book states that the major aim audience are people who have some familiarity with Internet of things (IoT) but interested to get a comprehensive interpretation of the role of deep Learning in maintaining the security and privacy of IoT. A reader should be friendly with Python and the basics of machine learning and deep learning. Interpretation of statistics and probability theory will be a plus but is not certainly vital for identifying most of the book's material.

The book features original papers from International Conference on Cryptology & Network Security with Machine Learning (ICCNSML 2022), organized by PSIT, Kanpur, India during 16 – 18 December 2022. This conference proceeding will provide the understanding of core concepts of Cryptology & Network Security with ML in data communication. The book covers research papers in public key cryptography, elliptic curve cryptography, post quantum cryptography, lattice based cryptography, non-commutative ring based cryptography, cryptocurrency, authentication, key agreement, Hash functions, block/stream ciphers, polynomial based cryptography, code based cryptography, NTRU cryptosystems, security and privacy in machine learning, block chain, IoT security, wireless security protocols, cryptanalysis, number theory, quantum computing, cryptographic aspects of network security, complexity theory, and cryptography with machine learning.