AI-Embedded Blockchain Technologies and Applications : Enhancing Cybersecurity Systems in Smart Environments

Enables readers to understand how machine learning and blockchain technologies can enhance cybersecurity of systems in smart and intelligent environments. AI-Embedded Blockchain Technologies and Applications: Enhancing Cybersecurity Systems in Smart Environments explores the intersection of two cutting-edge technologies, machine learning and blockchain, and their potential to enhance the cybersecurity of systems in smart and intelligent environments. This book also delivers expert insight and practical tips on emerging trends and recent advancements in the fields of artificial intelligence, cyber security, smart healthcare, and smart cities. The book begins with an introduction to the growing challenges of cybersecurity in smart and intelligent environments, highlighting the increasing complexity and interconnectedness of modern systems which leads to vulnerabilities and the need for innovative solutions. From there, the book provides an expansive overview of each technology, with key insight into how they can be used together to achieve superior performance. Real-world case studies and practical implementations of covered technologies are included throughout, with information on implementation challenges, benefits, lessons learned, and much more. Edited by three highly qualified academics and contributed to by leaders in the field, AI-Embedded Blockchain Technologies and Applications: Enhancing Cybersecurity Systems in Smart Environments covers sample topics, including: Supervised and unsupervised learning, classification, regression, clustering, deep learning, neural networks, and reinforcement learningCybersecurity, cloud, secure data storage, identity management, secure communication protocols, intrusion detection, malware analysis, anomaly detection, and threat intelligenceFundamental components of a blockchain such as blocks, transactions, consensus mechanisms, cryptographic hashing, and smart contractsBlockchain scalability, privacy-preserving techniques, and the integration of other technologies such as Internet of Things (IoT) and edge computing. Written in accessible language and bridging the gap between theory and practice, AI-Embedded Blockchain Technologies and Applications: Enhancing Cybersecurity Systems in Smart Environments is an essential resource on secure, smart and intelligent environments for specialists, analysts, engineers, scholars, and researchers in related fields.

Enables readers to understand how machine learning and blockchain technologies can enhance cybersecurity of systems in smart and intelligent environments.

AI-Embedded Blockchain Technologies and Applications: Enhancing Cybersecurity Systems in Smart Environments explores the intersection of two cutting-edge technologies, machine learning and blockchain, and their potential to enhance the cybersecurity of systems in smart and intelligent environments. This book also delivers expert insight and practical tips on emerging trends and recent advancements in the fields of artificial intelligence, cyber security, smart healthcare, and smart cities.

The book begins with an introduction to the growing challenges of cybersecurity in smart and intelligent environments, highlighting the increasing complexity and interconnectedness of modern systems which leads to vulnerabilities and the need for innovative solutions. From there, the book provides an expansive overview of each technology, with key insight into how they can be used together to achieve superior performance.

Real-world case studies and practical implementations of covered technologies are included throughout, with information on implementation challenges, benefits, lessons learned, and much more.

Edited by three highly qualified academics and contributed to by leaders in the field, AI-Embedded Blockchain Technologies and Applications: Enhancing Cybersecurity Systems in Smart Environments covers sample topics, including:

• Supervised and unsupervised learning, classification, regression, clustering, deep learning, neural networks, and reinforcement learning
• Cybersecurity, cloud, secure data storage, identity management, secure communication protocols, intrusion detection, malware analysis, anomaly detection, and threat intelligence
• Fundamental components of a blockchain such as blocks, transactions, consensus mechanisms, cryptographic hashing, and smart contracts
• Blockchain scalability, privacy-preserving techniques, and the integration of other technologies such as Internet of Things (IoT) and edge computing.

Written in accessible language and bridging the gap between theory and practice, AI-Embedded Blockchain Technologies and Applications: Enhancing Cybersecurity Systems in Smart Environments is an essential resource on secure, smart and intelligent environments for specialists, analysts, engineers, scholars, and researchers in related fields.