This reference reviews the architectural requirements of IT systems that are designed to digitally transform business operations. It is a compilation of 7 timely reviews that demonstrate how adopting emerging technologies and examining the security-based concerns can lead to innovation in the business sector. The aim of the book is to guide scholars and business consultants on IT and business frameworks that can help new and existing organizations navigate the challenges posed by disruptive technologies to create a competitive advantage. The reviews are contributed by experts in business and information technology. The chapters cover diverse topics related to technological advancements and digital security measures. Chapter 1 offers insights into accessing and securing patient medical records through a blockchain-based framework, detailing research methodology, scalability, and standards. Chapter 2 discusses cyber threats in IoT-connected cars, addressing vulnerabilities, attack methods, and defense strategies. Chapter 3 focuses on malware analysis and detection using machine learning techniques. Chapter 4 emphasizes on securing IoT-based home automation. Chapter 5 presents an IoT policy and governance reference architecture to ensure integrity and security across devices. Chapter 6 explores organizational security improvements to prevent deepfake ransomware. Finally, Chapter 7 examines the use of machine learning in credit card fraud detection, discussing challenges and control layers.

This book offers comprehensive insights into digital forensics, guiding readers through analysis methods and security assessments. Expert contributors cover a range of forensic investigations on computer devices, making it an essential resource for professionals, scholars, and students alike. Chapter 1 explores smart home forensics, detailing IoT forensic analysis and examination of different smart home devices. Chapter 2 provides an extensive guide to digital forensics, covering its origin, objectives, tools, challenges, and legal considerations. Chapter 3 focuses on cyber forensics, including secure chat application values and experimentation. Chapter 4 delves into browser analysis and exploitation techniques, while Chapter 5 discusses data recovery from water-damaged Android phones with methods and case studies. Finally, Chapter 6 presents a machine learning approach for detecting ransomware threats in healthcare systems. With a reader-friendly format and practical case studies, this book equips readers with essential knowledge for cybersecurity services and operations. Key Features: 1.Integrates research from various fields (IoT, Big Data, AI, and Blockchain) to explain smart device security. 2.Uncovers innovative features of cyber forensics and smart devices. 3.Harmonizes theoretical and practical aspects of cybersecurity. 4.Includes chapter summaries and key concepts for easy revision. 5.Offers references for further study.

This book explores the intersection of the Internet of Things (IoT) and Artificial Intelligence (AI) in sustaining a green environment, sustainable societies, and thriving industries. It offers a comprehensive exploration of how these technologies intersect and transform various sectors to enhance environmental conservation, societal well-being, and industrial progress. The book features a diverse array of case studies, methodologies, and notes on technological advancements. Readers will gain valuable insights into the impact of AI and IoT on sustainable initiatives through real-world examples, research findings, and discussions on future directions. Key themes AI in complex and versatile scenarios: Chapters 1 and 4 explore AI applications in combatant identification and COVID-19 monitoring IoT for efficiency and data-driven decision-making: Chapters 2, 3, and 7 focus on IoT implementations in battery monitoring for electric vehicles, healthcare systems, and precision farming AI for diagnostics and computer vision: Chapters 5, 9, and 13 highlight AI-driven solutions for plant disease detection, fetal spine disorder detection, and defect detection Industry applications: Chapters 6, 8, 10, 11, 12, 14, 15, 16, and 17 cover AI and IoT in healthcare, transportation, supply chain management, endangered species protection, crop management, and pollution detection, showcasing their transformative potential across various domains. This book is ideal for readers with multidisciplinary backgrounds, including researchers, academics, professionals, and students interested in IoT, AI, environmental sustainability, healthcare, agriculture, smart technologies, and industrial innovation.

This handbook provides a comprehensive understanding of computational linguistics, focusing on the integration of deep learning in natural language processing (NLP). 18 edited chapters cover the state-of-the-art theoretical and experimental research on NLP, offering insights into advanced models and recent applications. Highlights: - Foundations of NLP: Provides an in-depth study of natural language processing, including basics, challenges, and applications. - Advanced NLP Techniques: Explores recent advancements in text summarization, machine translation, and deep learning applications in NLP. - Practical Applications: Demonstrates use cases on text identification from hazy images, speech-to-sign language translation, and word sense disambiguation using deep learning. - Future Directions: Includes discussions on the future of NLP, including transfer learning, beyond syntax and semantics, and emerging challenges. Key Features: - Comprehensive coverage of NLP and deep learning integration. - Practical insights into real-world applications - Detailed exploration of recent research and advancements through 16 easy to read chapters - References and notes on experimental methods used for advanced readers Ideal for researchers, students, and professionals, this book offers a thorough understanding of computational linguistics by equipping readers with the knowledge to understand how computational techniques are applied to understand text, language and speech.

This book demonstrates several use cases of how artificial intelligence (AI) and machine learning (ML) are revolutionizing problem-solving across various industries. The book presents 18 edited chapters beginning with the latest advancements in human-AI interactions and neuromorphic computing, setting the stage for practical applications. Chapters focus on AI and ML applications such as fingerprint recognition, glaucoma detection, and lung cancer identification using image processing. The book also explores the role of AI in professional operations such as UX design, event detection, and content analysis. Additionally, the book includes content that examines AI's impact on technical operations wireless communication, VLSI systems, and advanced manufacturing processes. Each chapter contains summaries and references for addressing the needs of beginner and advanced readers. This comprehensive guide is an essential resource for anyone seeking to understand AI's transformative role in modern problem-solving in professional industries.

Smart Home and Industrial IoT Devices: Critical Perspectives on Cyber Threats, Frameworks and Protocols provides an in-depth examination of the Internet of Things (IoT) and its profound impact on smart homes and industrial systems. The book begins by exploring the significance of IoT in smart homes, followed by an analysis of emerging cyber threats targeting smart homes and cyber-physical systems. It presents AI and machine learning-based frameworks for monitoring water quality and managing irrigation in agriculture, highlighting their role in IoT ecosystems. The text also discusses a framework to mitigate cyber-attacks on robotic systems and introduces a multinomial naive Bayesian classifier for analyzing smart IoT devices. Dataflow analysis and modeling experiments are detailed, along with a comparison of IoT communication protocols using anomaly detection and security assessment. The book concludes with a discussion on efficient, lightweight intrusion detection systems and a unique taxonomy for IoT frameworks. This book is ideal for students, researchers, and professionals seeking to understand and secure IoT environments.

Artificial Intelligence: A Multidisciplinary Approach towards Teaching and Learning explores the evolving role of AI in education, covering applications in fields such as bioinformatics, environmental science, physics, chemistry, economics, and language learning. Written by experts, this book provides a comprehensive overview of AI's integration into diverse subjects, offering insights into the future of AI in education and its potential to enhance academic research and pedagogy. Targeted at faculty, students, and professionals, the book addresses AI's role in blended learning environments and offers practical tools for educators seeking to incorporate AI into their teaching practices. Key Features: - Multidisciplinary exploration of AI in teaching and learning. - Practical tools and methodologies for educators. - Insights into AI-driven innovations in research. - Relevant to a broad audience, from students to professionals.

The Future of Computing: Ubiquitous Applications and Technologies explores the transformative power of ubiquitous computing across diverse fields, from healthcare and smart grids to home automation and digital forensics. Ubiquitous computing, which seamlessly integrates computing into everyday life, is reshaping industries and addressing significant challenges, such as data security, digital payments, and IoT optimization. This book provides expert insights and practical approaches, covering topics such as automated medical imaging, federated cloud assessments, smart grid security, and AI-driven control systems. Key Features: - Foundational and advanced concepts of ubiquitous computing across multiple industries. - Security structures in IoT, AI applications, and data privacy. - Real-world applications, including healthcare automation, smart homes, and digital forensics. - Case studies on emerging trends in IoT, AIoT, and smart grid security.

Practical Digital Forensics: A Guide for Windows and Linux Users is a comprehensive resource for novice and experienced digital forensics investigators. This guide offers detailed step-by-step instructions, case studies, and real-world examples to help readers conduct investigations on both Windows and Linux operating systems. It covers essential topics such as configuring a forensic lab, live system analysis, file system and registry analysis, network forensics, and anti-forensic techniques. The book is designed to equip professionals with the skills to extract and analyze digital evidence, all while navigating the complexities of modern cybercrime and digital investigations. Key Features: - Forensic principles for both Linux and Windows environments. - Detailed instructions on file system forensics, volatile data acquisition, and network traffic analysis. - Advanced techniques for web browser and registry forensics. - Addresses anti-forensics tactics and reporting strategies.