As the progression of the internet continues, society is finding easier, quicker ways of simplifying their needs with the use of technology. With the growth of lightweight devices, such as smart phones and wearable devices, highly configured hardware is in heightened demand in order to process the large amounts of raw data that are acquired. Connecting these devices to fog computing can reduce bandwidth and latency for data transmission when associated with centralized cloud solutions and uses machine learning algorithms to handle large amounts of raw data. The risks that accompany this advancing technology, however, have yet to be explored. Architecture and Security Issues in Fog Computing Applications is a pivotal reference source that provides vital research on the architectural complications of fog processing and focuses on security and privacy issues in intelligent fog applications. While highlighting topics such as machine learning, cyber-physical systems, and security applications, this publication explores the architecture of intelligent fog applications enabled with machine learning. This book is ideally designed for IT specialists, software developers, security analysts, software engineers, academicians, students, and researchers seeking current research on network security and wireless systems.

The internet of things (IoT) has drawn great attention from both academia and industry, since it offers a challenging notion of creating a world where all things around us are connected to the internet and communicate with each other with minimal human intervention. Another component for helping IoT to succeed is cloud computing. The combination of cloud computing and IoT will enable new monitoring services and powerful processing of sensory data streams. These applications, alongside implementation details and challenges, should also be explored for successful mainstream adoption. IoT is also fueled by the advancement of digital technologies, and the next generation era will be cloud-based IoT systems. Integration and Implementation of the Internet of Things Through Cloud Computing studies, analyzes, and presents cloud-based IoT-related technologies, protocols, and standards along with recent research and development in cloud-based IoT. It also presents recent emerging trends and technological advances of cloud-based IoT, innovative applications, and the challenges and implications for society. The chapters included take a strong look at the societal and social aspects of this technology along with its implementations and technological analyses. This book is intended for IT specialists, technologists, practitioners, researchers, academicians, and students who are interested in the next era of IoT through cloud computing.

Securing Delay-Tolerant Networks with BPSec One-stop reference on how to secure a Delay-Tolerant Network (DTN), written by experienced industry insiders Securing Delay-Tolerant Networks with BPSec answers the question, "How can delay-tolerant networks be secured when operating in environments that would otherwise break many of the common security approaches used on the terrestrial Internet today?" The text is composed of three sections: (1) security considerations for delay-tolerant networks, (2) the design, implementation, and customization of the BPSec protocol, and (3) how this protocol can be applied, combined with other security protocols, and deployed in emerging network environments. The text includes pragmatic considerations for deploying BPSec in both regular and delay-tolerant networks. It also features a tutorial on how to achieve several important security outcomes with a combination of security protocols, BPSec included. Overall, it covers best practices for common security functions, clearly showing designers how to prevent network architecture from being over-constrained by traditional security approaches. Written by the lead author and originator of the BPSec protocol specification, Securing Delay-Tolerant Networks (DTNs) with BPSec includes information on: The gap between cryptography and network security, how security requirements constrain network architectures, and why we need something different DTN stressing conditions, covering intermittent connectivity, congested paths, partitioned topologies, limited link state, and multiple administrative controls Securing the terrestrial internet, involving a layered approach to security, the impact of protocol design on security services, and securing the internetworking and transport layers A delay-tolerant security architecture, including desirable properties of a DTN secure protocol, fine-grained security services, and protocol augmentation Securing Delay-Tolerant Networks (DTNs) with BPSec is a one-stop reference on the subject for any professional operationally deploying BP who must use BPSec for its security, including software technical leads, software developers, space flight mission leaders, network operators, and technology and product development leaders in general.

The COVID-19 pandemic has forced organizations and individuals to embrace new practices such as social distancing and remote working. During these unprecedented times, many have increasingly relied on the internet for work, shopping, and healthcare. However, while the world focuses on the health and economic threats posed by the COVID-19 pandemic, cyber criminals are capitalizing on this crisis as the world has become more digitally dependent and vulnerable than ever. Cybersecurity Crisis Management and Lessons Learned From the COVID-19 Pandemic provides cutting-edge research on the best guidelines for preventing, detecting, and responding to cyber threats within educational, business, health, and governmental organizations during the COVID-19 pandemic. It further highlights the importance of focusing on cybersecurity within organizational crisis management. Covering topics such as privacy and healthcare, remote work, and personal health data, this premier reference source is an indispensable resource for startup companies, health and business executives, ICT procurement managers, IT professionals, libraries, students and educators of higher education, entrepreneurs, government officials, social media experts, researchers, and academicians.

Distributed systems intertwine with our everyday lives. The benefits and current shortcomings of the underpinning technologies are experienced by a wide range of people and their smart devices. With the rise of large-scale IoT and similar distributed systems, cloud bursting technologies, and partial outsourcing solutions, private entities are encouraged to increase their efficiency and offer unparalleled availability and reliability to their users. Applying Integration Techniques and Methods in Distributed Systems is a critical scholarly publication that defines the current state of distributed systems, determines further goals, and presents architectures and service frameworks to achieve highly integrated distributed systems and presents solutions to integration and efficient management challenges faced by current and future distributed systems. Highlighting topics such as multimedia, programming languages, and smart environments, this book is ideal for system administrators, integrators, designers, developers, researchers, and academicians.

Many professional fields have been affected by the rapid growth of technology and information. Included in this are the business and management markets as the implementation of e-commerce and cloud computing have caused enterprises to make considerable changes to their practices. With the swift advancement of this technology, professionals need proper research that provides solutions to the various issues that come with data integration and shifting to a technology-driven environment. Cloud Computing Applications and Techniques for E-Commerce is an essential reference source that discusses the implementation of data and cloud technology within the fields of business and information management. Featuring research on topics such as content delivery networks, virtualization, and software resources, this book is ideally designed for managers, educators, administrators, researchers, computer scientists, business practitioners, economists, information analysists, sociologists, and students seeking coverage on the recent advancements of e-commerce using cloud computing techniques.

In recent years, falsification and digital modification of video clips, images, as well as textual contents have become widespread and numerous, especially when deepfake technologies are adopted in many sources. Due to adopted deepfake techniques, a lot of content currently cannot be recognized from its original sources. As a result, the field of study previously devoted to general multimedia forensics has been revived. The Handbook of Research on Advanced Practical Approaches to Deepfake Detection and Applications discusses the recent techniques and applications of illustration, generation, and detection of deepfake content in multimedia. It introduces the techniques and gives an overview of deepfake applications, types of deepfakes, the algorithms and applications used in deepfakes, recent challenges and problems, and practical applications to identify, generate, and detect deepfakes. Covering topics such as anomaly detection, intrusion detection, and security enhancement, this major reference work is a comprehensive resource for cyber security specialists, government officials, law enforcement, business leaders, students and faculty of higher education, librarians, researchers, and academicians.

Deep Learning through Sparse Representation and Low-Rank Modeling bridges classical sparse and low rank models-those that emphasize problem-specific Interpretability-with recent deep network models that have enabled a larger learning capacity and better utilization of Big Data. It shows how the toolkit of deep learning is closely tied with the sparse/low rank methods and algorithms, providing a rich variety of theoretical and analytic tools to guide the design and interpretation of deep learning models. The development of the theory and models is supported by a wide variety of applications in computer vision, machine learning, signal processing, and data mining. This book will be highly useful for researchers, graduate students and practitioners working in the fields of computer vision, machine learning, signal processing, optimization and statistics.

If you look around you will find that all computer systems, from your portable devices to the strongest supercomputers, are heterogeneous in nature. The most obvious heterogeneity is the existence of computing nodes of different capabilities (e.g. multicore, GPUs, FPGAs, ...). But there are also other heterogeneity factors that exist in computing systems, like the memory system components, interconnection, etc. The main reason for these different types of heterogeneity is to have good performance with power efficiency. Heterogeneous computing results in both challenges and opportunities. This book discusses both. It shows that we need to deal with these challenges at all levels of the computing stack: from algorithms all the way to process technology. We discuss the topic of heterogeneous computing from different angles: hardware challenges, current hardware state-of-the-art, software issues, how to make the best use of the current heterogeneous systems, and what lies ahead. The aim of this book is to introduce the big picture of heterogeneous computing. Whether you are a hardware designer or a software developer, you need to know how the pieces of the puzzle fit together. The main goal is to bring researchers and engineers to the forefront of the research frontier in the new era that started a few years ago and is expected to continue for decades. We believe that academics, researchers, practitioners, and students will benefit from this book and will be prepared to tackle the big wave of heterogeneous computing that is here to stay.

Businesses have had to face many challenges due to the COVID-19 pandemic; to survive in the changing landscape, they had to adapt quickly and implement new tactics and best practices to stay competitive. Networking is one of the many areas that looks vastly different in a post-pandemic world and companies must understand this change or risk falling behind. Further study is required to uncover the various difficulties and potential future directions of networking and innovation within the business landscape. The Handbook of Research on Digital Innovation and Networking in Post-COVID-19 Organizations provides a thorough overview of the ways in which organizations have had to change and adapt to the new business environments and considers how networking looks different in a post-COVID-19 world. Covering key topics such as organizational structures, consumer behavior, teleworking, and collaborations, this major reference work is ideal for managers, business owners, industry professionals, policymakers, researchers, scholars, academicians, practitioners, instructors, and students.

Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications covers timely topics, including the neural network (NN), particle swarm optimization (PSO), evolutionary algorithm (GA), fuzzy sets (FS) and rough sets (RS), etc. Furthermore, the book highlights recent research on representative techniques to elaborate how a data-centric system formed a powerful platform for the processing of cloud hosted multimedia big data and how it could be analyzed, processed and characterized by CI. The book also provides a view on how techniques in CI can offer solutions in modeling, relationship pattern recognition, clustering and other problems in bioengineering. It is written for domain experts and developers who want to understand and explore the application of computational intelligence aspects (opportunities and challenges) for design and development of a data-centric system in the context of multimedia cloud, big data era and its related applications, such as smarter healthcare, homeland security, traffic control trading analysis and telecom, etc. Researchers and PhD students exploring the significance of data centric systems in the next paradigm of computing will find this book extremely useful.

Digital technologies are currently dramatically changing healthcare. Cloud healthcare is an increasingly trending topic in the field, converging skills from computer and health science. This new strategy fosters the management of health data at a large scale and makes it easier for healthcare organizations to improve patient experience and health team productivity while helping the support, security, compliance, and interoperability of health data. Exploring the Convergence of Computer and Medical Science Through Cloud Healthcare is a reference in the ongoing digital transformation of the healthcare sector. It presents a comprehensive state-of-the-art approach to cloud internet of things health technologies and practices. It provides insights over strategies, methodologies, techniques, tools, and services based on emerging cloud digital health solutions to overcome digital health challenges. Covering topics such as auxiliary systems, the internet of medical things, and natural language processing, this premier reference source is an essential resource for medical professionals, hospital administrators, medical students, medical professors, libraries, researchers, and academicians.

Society is continually transforming into a digitally powered reality due to the increased dependence of computing technologies. The landscape of cyber threats is constantly evolving because of this, as hackers are finding improved methods of accessing essential data. Analyzing the historical evolution of cyberattacks can assist practitioners in predicting what future threats could be on the horizon. Real-Time and Retrospective Analyses of Cyber Security is a pivotal reference source that provides vital research on studying the development of cybersecurity practices through historical and sociological analyses. While highlighting topics such as zero trust networks, geopolitical analysis, and cyber warfare, this publication explores the evolution of cyber threats, as well as improving security methods and their socio-technological impact. This book is ideally designed for researchers, policymakers, strategists, officials, developers, educators, sociologists, and students seeking current research on the evolution of cybersecurity methods through historical analysis and future trends.