"This book explores current advances in digital and mobile computing technologies from the user perspective, evaluating trust models and autonomic trust management covering the recent history of trust in digital environments to prospective future developments"--Provided by publisher.

This is a monumental reference for the theory and practice of computer security. Comprehensive in scope, this text covers applied and practical elements, theory, and the reasons for the design of applications and security techniques. It covers both the management and the engineering issues of computer security. It provides excellent examples of ideas and mechanisms that demonstrate how disparate techniques and principles are combined in widely-used systems. This book is acclaimed for its scope, clear and lucid writing, and its combination of formal and theoretical aspects with real systems, technologies, techniques, and policies.

Technology trends may come and go, but cloud computing technologies have been gaining consideration in the commercial world due to its ability to provide on-demand access to resources, control the software environment, and supplement existing systems. Pervasive Cloud Computing Technologies: Future Outlooks and Interdisciplinary Perspectives explores the latest innovations with cloud computing and the impact of these new models and technologies. This book will present case studies and research on the future of cloud computing technologies and its ability to increase connectivity of various entities of the world. It is an essential resource for technology practitioners, engineers, managers, and academics aiming to gain the knowledge of these novel and pervasive technologies.

Operations management is a tool by which companies can effectively meet customers’ needs using the least amount of resources necessary. With the emergence of sensors and smart metering, big data is becoming an intrinsic part of modern operations management. Applied Big Data Analytics in Operations Management enumerates the challenges and creative solutions and tools to apply when using big data in operations management. Outlining revolutionary concepts and applications that help businesses predict customer behavior along with applications of artificial neural networks, predictive analytics, and opinion mining on business management, this comprehensive publication is ideal for IT professionals, software engineers, business professionals, managers, and students of management.

Patterns can be any number of items that occur repeatedly, whether in the behaviour of animals, humans, traffic, or even in the appearance of a design. As technologies continue to advance, recognizing, mimicking, and responding to all types of patterns becomes more precise. Pattern Recognition and Classification in Time Series Data focuses on intelligent methods and techniques for recognizing and storing dynamic patterns. Emphasizing topics related to artificial intelligence, pattern management, and algorithm development, in addition to practical examples and applications, this publication is an essential reference source for graduate students, researchers, and professionals in a variety of computer-related disciplines.

Handbook of Digital Finance and Financial Inclusion: Cryptocurrency, FinTech, InsurTech, Regulation, ChinaTech, Mobile Security, and Distributed Ledger explores recent advances in digital banking and cryptocurrency, emphasizing mobile technology and evolving uses of cryptocurrencies as financial assets. Contributors go beyond summaries of standard models to describe new banking business models that will be sustainable and likely to dictate the future of finance. The book not only emphasizes the financial opportunities made possible by digital banking, such as financial inclusion and impact investing, but also looks at engineering theories and developments that encourage innovation. Its ability to illuminate present potential and future possibilities make it a unique contribution to the literature. A companion Volume Two of The Handbook of Digital Banking and Financial Inclusion: ChinaTech, Mobile Security, Distributed Ledger, and Blockchain emphasizes technological developments that introduce the future of finance. Descriptions of recent innovations lay the foundations for explorations of feasible solutions for banks and startups to grow. The combination of studies on blockchain technologies and applications, regional financial inclusion movements, advances in Chinese finance, and security issues delivers a grand perspective on both changing industries and lifestyles. Written for students and practitioners, it helps lead the way to future possibilities. - Explains the practical consequences of both technologies and economics to readers who want to learn about subjects related to their specialties - Encompasses alternative finance, financial inclusion, impact investing, decentralized consensus ledger and applied cryptography - Provides the only advanced methodical summary of these subjects available today

Many techniques have been developed to control the variety of dynamic systems. To develop those control techniques, it is fundamental to know the mathematical relations between the system inputs and outputs. Incorporating Nature-Inspired Paradigms in Computational Applications is a critical scholarly resource that examines the application of nature-inspired paradigms on system identification. Featuring coverage on a broad range of topics such as biogeographic computation, evolutionary control systems, and natural computing, this book is geared towards IT professionals, engineers, computer scientists, academicians, researchers, and graduate-level students seeking current research on the application of nature-inspired paradigms.

"This book provides the latest empirical research and theoretical frameworks in the area of information security, presenting research on developing sufficient security measures for new environments by discussing challenges faced by researchers as well as unconventional solutions to these problems"--Provided by publisher.

In the digital era, information is the most valuable resource, and protecting one’s assets is a constant struggle for both individuals and organizations. Analyzing Security, Trust, and Crime in the Digital World explores techniques and technologies used to secure data and prevent intrusion in virtual environments. Within these pages, computer scientists, programmers, engineers, and practitioners will find meaningful research on intrusion detection and authentication techniques in order to further defend their own systems and protect the information therein.

Comprehensive resource providing strategic defense mechanisms for malware, handling cybercrime, and identifying loopholes using artificial intelligence (AI) and machine learning (ML) Applying Artificial Intelligence in Cyber Security Analytics and Cyber Threat Detection is a comprehensive look at state-of-the-art theory and practical guidelines pertaining to the subject, showcasing recent innovations, emerging trends, and concerns as well as applied challenges encountered, and solutions adopted in the fields of cybersecurity using analytics and machine learning. The text clearly explains theoretical aspects, framework, system architecture, analysis and design, implementation, validation, and tools and techniques of data science and machine learning to detect and prevent cyber threats. Using AI and ML approaches, the book offers strategic defense mechanisms for addressing malware, cybercrime, and system vulnerabilities. It also provides tools and techniques that can be applied by professional analysts to safely analyze, debug, and disassemble any malicious software they encounter. With contributions from qualified authors with significant experience in the field, Applying Artificial Intelligence in Cyber Security Analytics and Cyber Threat Detection explores topics such as: Cybersecurity tools originating from computational statistics literature and pure mathematics, such as nonparametric probability density estimation, graph-based manifold learning, and topological data analysis Applications of AI to penetration testing, malware, data privacy, intrusion detection system (IDS), and social engineering How AI automation addresses various security challenges in daily workflows and how to perform automated analyses to proactively mitigate threats Offensive technologies grouped together and analyzed at a higher level from both an offensive and defensive standpoint Providing detailed coverage of a rapidly expanding field, Applying Artificial Intelligence in Cyber Security Analytics and Cyber Threat Detection is an essential resource for a wide variety of researchers, scientists, and professionals involved in fields that intersect with cybersecurity, artificial intelligence, and machine learning.