This book first discusses cyber security fundamentals then delves into security threats and vulnerabilities, security vigilance, and security engineering for Internet of Everything (IoE) networks. After an introduction, the first section covers the security threats and vulnerabilities or techniques to expose the networks to security attacks such as repudiation, tampering, spoofing, and elevation of privilege. The second section of the book covers vigilance or prevention techniques like intrusion detection systems, trust evaluation models, crypto, and hashing privacy solutions for IoE networks. This section also covers the security engineering for embedded and cyber-physical systems in IoE networks such as blockchain, artificial intelligence, and machine learning-based solutions to secure the networks. This book provides a clear overview in all relevant areas so readers gain a better understanding of IoE networks in terms of security threats, prevention, and other security mechanisms.

In this comprehensive and cutting-edge volume, Qureshi and Jeon bring together experts from around the world to explore the potential of artificial intelligence models in research and discuss the potential benefits and the concerns and challenges that the rapid development of this field has raised. The international chapter contributor group provides a wealth of technical information on different aspects of AI, including key aspects of AI, deep learning and machine learning models for AI, natural language processing and computer vision, reinforcement learning, ethics and responsibilities, security, practical implementation, and future directions. The contents are balanced in terms of theory, methodologies, and technical aspects, and contributors provide case studies to clearly illustrate the concepts and technical discussions throughout. Readers will gain valuable insights into how AI can revolutionize their work in fields including data analytics and pattern identification, healthcare research, social science research, and more, and improve their technical skills, problem-solving abilities, and evidence-based decision-making. Additionally, they will be cognizant of the limitations and challenges, the ethical implications, and security concerns related to language models, which will enable them to make more informed choices regarding their implementation. This book is an invaluable resource for undergraduate and graduate students who want to understand AI models, recent trends in the area, and technical and ethical aspects of AI. Companies involved in AI development or implementing AI in various fields will also benefit from the book’s discussions on both the technical and ethical aspects of this rapidly growing field.

In today’s interconnected world, healthcare systems are increasingly turning to digital technologies to enhance patient care and optimize operations. However, this digital transformation presents significant challenges in guaranteeing the security and privacy of sensitive healthcare data. Secure Health: A Guide to Cybersecurity for Healthcare Managers confronts these challenges head-on, offering a comprehensive exploration of the latest advancements and best practices in securing digital health systems. From examining the convergence of Internet of Things (IoT) applications with healthcare privacy and security to investigating ethical hacking frameworks and biometric access management, each chapter delves into valuable insights for safeguarding healthcare data in an ever-more digitized landscape. What sets this book apart is its holistic perspective, encompassing not only technical aspects but also governance standards, the unique cybersecurity challenges of telehealth, and the optimization of healthcare supply chain management. KEY FEATURES: • Explores the integration of IoT devices into healthcare and the associated privacy and security risks. • Examines security frameworks and best practices for e-health information governance. • Introduces a novel framework for ethical hacking in digital health. • Analyzes the effectiveness of different artificial intelligence (AI) models for botnet traffic classification. • Delves into the unique challenges of securing telehealth and remote monitoring systems. • Offers practical guidance on securing the future of e-health through smart sensor network management.

Cyber threats are ever increasing. Adversaries are getting more sophisticated and cyber criminals are infiltrating companies in a variety of sectors. In today’s landscape, organizations need to acquire and develop effective security tools and mechanisms – not only to keep up with cyber criminals, but also to stay one step ahead. Cyber-Vigilance and Digital Trust develops cyber security disciplines that serve this double objective, dealing with cyber security threats in a unique way. Specifically, the book reviews recent advances in cyber threat intelligence, trust management and risk analysis, and gives a formal and technical approach based on a data tainting mechanism to avoid data leakage in Android systems

This textbook presents a proven, mature Model-Based Systems Engineering (MBSE) methodology that has delivered success in a wide range of system and enterprise programs. The authors introduce MBSE as the state of the practice in the vital Systems Engineering discipline that manages complexity and integrates technologies and design approaches to achieve effective, affordable, and balanced system solutions to the needs of a customer organization and its personnel. The book begins with a summary of the background and nature of MBSE. It summarizes the theory behind Object-Oriented Design applied to complex system architectures. It then walks through the phases of the MBSE methodology, using system examples to illustrate key points. Subsequent chapters broaden the application of MBSE in Service-Oriented Architectures (SOA), real-time systems, cybersecurity, networked enterprises, system simulations, and prototyping. The vital subject of system and architecture governance completes the discussion. The book features exercises at the end of each chapter intended to help readers/students focus on key points, as well as extensive appendices that furnish additional detail in particular areas. The self-contained text is ideal for students in a range of courses in systems architecture and MBSE as well as for practitioners seeking a highly practical presentation of MBSE principles and techniques.