Digital transformation in organizations optimizes the business processes but also brings additional challenges in the form of security threats and vulnerabilities. Cyberattacks incur financial losses for organizations and can affect their reputations. Due to this, cybersecurity has become critical for business enterprises. Extensive technological adoption in businesses and the evolution of FinTech applications require reasonable cybersecurity measures to protect organizations from internal and external security threats. Recent advances in the cybersecurity domain such as zero trust architecture, application of machine learning, and quantum and post-quantum cryptography have colossal potential to secure technological infrastructures. Cybersecurity Issues and Challenges for Business and FinTech Applications discusses theoretical foundations and empirical studies of cybersecurity implications in global digital transformation and considers cybersecurity challenges in diverse business areas. Covering essential topics such as artificial intelligence, social commerce, and data leakage, this reference work is ideal for cybersecurity professionals, business owners, managers, policymakers, researchers, scholars, academicians, practitioners, instructors, and students.

Wireless communication is continuously evolving to improve and be a part of our daily communication. This leads to improved quality of services and applications supported by networking technologies. We are now able to use LTE, LTE-Advanced, and other emerging technologies due to the enormous efforts that are made to improve the quality of service in cellular networks. As the future of networking is uncertain, the use of deep learning and big data analytics is a point of focus as it can work in many capacities at a variety of levels for wireless communications. Implementing Data Analytics and Architectures for Next Generation Wireless Communications addresses the existing and emerging theoretical and practical challenges in the design, development, and implementation of big data algorithms, protocols, architectures, and applications for next generation wireless communications and their applications in smart cities. The chapters of this book bring together academics and industrial practitioners to exchange, discuss, and implement the latest innovations and applications of data analytics in advanced networks. Specific topics covered include key encryption techniques, smart home appliances, fog communication networks, and security in the internet of things. This book is valuable for technologists, data analysts, networking experts, practitioners, researchers, academicians, and students.

The Blockchain Technology for Secure and Smart Applications across Industry Verticals, Volume 121, presents the latest information on a type of distributed ledger used for maintaining a permanent and tamper-proof record of transactional data. The book presents a novel compendium of existing and budding Blockchain technologies for various smart applications. Chapters in this new release include the Basics of Blockchain, The Blockchain History, Architecture of Blockchain, Core components of Blockchain, Blockchain 2.0: Smart Contracts, Empowering Digital Twins with Blockchain, Industrial Use Cases at the Cusp of the IoT and Blockchain Paradigms, Blockchain Components and Concepts, Digital Signatures, Accumulators, Financial Systems, and more. This book is a unique effort to illuminate various techniques to represent, improve and authorize multi-institutional and multidisciplinary research in a different type of smart applications, like the financial system, smart grid, transportation system, etc. Readers in identity-privacy, traceability, immutability, transparency, auditability, and security will find it to be a valuable resource.

The deterioration of water quality and unavailability of drinkable water are pressing challenges worldwide. The removal of toxic organic and inorganic pollutants from water is vital for a clean environment, as a response to water scarcity. Adsorption-based water technologies are among the most widely used because of their high efficiency and low cost, without relying on a complex infrastructure. In recent years, carbon nanomaterials (CNMs), such as graphene and derivatives, carbon nanotubes, carbon nanofibers, nanoporous carbon, fullerenes, graphitic carbon nitride, and nanodiamonds have been extensively exploited as adsorbents due to their extraordinary surface properties, ease of modification, large surface area, controlled structural varieties, high chemical stability, porosity, low density, ease of regeneration, and reusability. This book provides a thorough overview of the state of the art in carbon nanomaterials as they are used for adsorption applications in water purifications, as well as addressing their toxicological challenges. This volume primarily explores the fundamentals of adsorption, its mechanical aspects, synthesis and properties of CNMs, and adsorption performances of CNMs and their nanocomposites with organic and inorganic materials. Structural engineering and activation processes produce materials with enhanced adsorptive properties and separation efficiencies. Furthermore, the formation of CNMs with 2D and 3D macro-and microstructures and high porosities is a potential approach to improve adsorption performances and extend CNM use at the industrial level. The book also addresses important issues regarding these adsorbents that potentially affect future research and industrial applications of carbon-based nanoadsorbents in water security.

The concept of quantum computing is based on two fundamental principles of quantum mechanics: superposition and entanglement. Instead of using bits, qubits are used in quantum computing, which is a key indicator in the high level of safety and security this type of cryptography ensures. If interfered with or eavesdropped in, qubits will delete or refuse to send, which keeps the information safe. This is vital in the current era where sensitive and important personal information can be digitally shared online. In computer networks, a large amount of data is transferred worldwide daily, including anything from military plans to a country's sensitive information, and data breaches can be disastrous. This is where quantum cryptography comes into play. By not being dependent on computational power, it can easily replace classical cryptography. Limitations and Future Applications of Quantum Cryptography is a critical reference that provides knowledge on the basics of IoT infrastructure using quantum cryptography, the differences between classical and quantum cryptography, and the future aspects and developments in this field. The chapters cover themes that span from the usage of quantum cryptography in healthcare, to forensics, and more. While highlighting topics such as 5G networks, image processing, algorithms, and quantum machine learning, this book is ideally intended for security professionals, IoT developers, computer scientists, practitioners, researchers, academicians, and students interested in the most recent research on quantum computing.

This book addresses the issues with privacy and security in Internet of things (IoT) networks which are susceptible to cyber-attacks and proposes deep learning-based approaches using artificial neural networks models to achieve a safer and more secured IoT environment. Due to the inadequacy of existing solutions to cover the entire IoT network security spectrum, the book utilizes artificial neural network models, which are used to classify, recognize, and model complex data including images, voice, and text, to enhance the level of security and privacy of IoT. This is applied to several IoT applications which include wireless sensor networks (WSN), meter reading transmission in smart grid, vehicular ad hoc networks (VANET), industrial IoT and connected networks. The book serves as a reference for researchers, academics, and network engineers who want to develop enhanced security and privacy features in the design of IoT systems.

This book presents intelligent data analysis as a tool to fight against COVID-19 pandemic. The intelligent data analysis includes machine learning, natural language processing, and computer vision applications to teach computers to use big data-based models for pattern recognition, explanation, and prediction. These functions are discussed in detail in the book to recognize (diagnose), predict, and explain (treat) COVID-19 infections, and help manage socio-economic impacts. It also discusses primary warnings and alerts; tracking and prediction; data dashboards; diagnosis and prognosis; treatments and cures; and social control by the use of intelligent data analysis. It provides analysis reports, solutions using real-time data, and solution through web applications details.

Stem Cells: An Alternative Therapy for COVID-19 and Cytokine Storm provides mechanistic insights into the role of stem cells to combat COVID-19 outbreak and other pathologies where cytokines storm is the cause of concern for e.g., radiation exposure, multiple organ failure and sepsis. There has been an increase in number of cases of new diseases in the last decade, including mucormycosis, Zika virus, H1N1 influenza virus, among others. These diseases can be characterized by the induction of cytokine storm, which is mainly responsible for morbidity and mortality. Stem cell therapy has emerged as a potential treatment for viral diseases, including, but not limited to, COVID-19. Interestingly, clinical trials in patients with COVID-19 complications depicted faster recovery in patients post mesenchymal stem cells therapy owing to the decreased cytokines levels, anti-viral effects and regeneration of the infected tissue.

System on Chip Interfaces for Low Power Design provides a top-down understanding of interfaces available to SoC developers, not only the underlying protocols and architecture of each, but also how they interact and the tradeoffs involved. The book offers a common context to help understand the variety of available interfaces and make sense of technology from different vendors aligned with multiple standards. With particular emphasis on power as a factor, the authors explain how each interface performs in various usage scenarios and discuss their advantages and disadvantages. Readers learn to make educated decisions on what interfaces to use when designing systems and gain insight for innovating new/custom interfaces for a subsystem and their potential impact.

The development of software system with acceptable level of reliability and quality within available time frame and budget becomes a challenging objective. This objective could be achieved to some extent through early prediction of number of faults present in the software, which reduces the cost of development as it provides an opportunity to make early corrections during development process. The book presents an early software reliability prediction model that will help to grow the reliability of the software systems by monitoring it in each development phase, i.e. from requirement phase to testing phase. Different approaches are discussed in this book to tackle this challenging issue. An important approach presented in this book is a model to classify the modules into two categories (a) fault-prone and (b) not fault-prone. The methods presented in this book for assessing expected number of faults present in the software, assessing expected number of faults present at the end of each phase and classification of software modules in fault-prone or no fault-prone category are easy to understand, develop and use for any practitioner. The practitioners are expected to gain more information about their development process and product reliability, which can help to optimize the resources used.

Defining a new development life-cycle methodology, together with a set of associated techniques and tools to develop highly critical systems using formal techniques, this book adopts a rigorous safety assessment approach explored via several layers (from requirements analysis to automatic source code generation).

This is assessed and evaluated via a standard case study: the cardiac pacemaker. Additionally a formalisation of an Electrocardiogram (ECG) is used to identify anomalies in order to improve existing medical protocols. This allows the key issue - that formal methods are not currently integrated into established critical systems development processes - to be discussed in a highly effective and informative way.

"Using Event-B for Critical Device Software Systems" serves as a valuable resource for researchers and students of formal methods. The assessment of critical systems development is applicable to all industries, but engineers and physicians from the health domain will find the cardiac pacemaker case study of particular value.

Artificial Intelligence and Machine Learning for Predictive and Analytical Rendering in Edge Computing focuses on the role of AI and machine learning as it impacts and works alongside Edge Computing. Sections cover the growing number of devices and applications in diversified domains of industry, including gaming, speech recognition, medical diagnostics, robotics and computer vision and how they are being driven by Big Data, Artificial Intelligence, Machine Learning and distributed computing, may it be Cloud Computing or the evolving Fog and Edge Computing paradigms. Challenges covered include remote storage and computing, bandwidth overload due to transportation of data from End nodes to Cloud leading in latency issues, security issues in transporting sensitive medical and financial information across larger gaps in points of data generation and computing, as well as design features of Edge nodes to store and run AI/ML algorithms for effective rendering.

Hospitals, medical practices and healthcare organizations are implementing new technologies at breakneck speed. Yet privacy and security considerations are often an afterthought, putting healthcare organizations at risk of data security and privacy issues, fines, damage to their reputations, with serious potential consequences for the patients. Electronic Health Record systems (EHRs) consist of clinical notes, patient listings, lab results, imaging results and screening tests. EHRs are growing in complexity over time and requiring increasing amounts of data storage. With the development of the IoT, the Cloud and Smart Cities frameworks, new privacy and security methods are being pursued to secure healthcare-based systems and platforms. Presenting a detailed framework as well as comparative case studies for security protection, data integrity, privacy preservation, scalability, and healthcare legislation, this edited volume covers state of the art research and addresses privacy and security methods and technologies for EHRs.

This book focuses on recent developments in the field of two-dimensional nanomaterials for environmental applications. Due to their high surface area and tunable surface chemistry, two-dimensional nanomaterials are currently garnering great interest for environmental remediation applications. This book compiles contributed chapters from active international researchers dealing with the development of state-of-the-art two-dimensional nanomaterials in environmental applications such as water and wastewater treatment, adsorption, photocatalysis, membrane separation, desalination, deionization, environmental pollutants sensing/detection, carbon-dioxide capture and catalytic conversion, microbial treatment, and electrochemical remediation.  Each chapter provides an essential and comprehensive overview of the recent advances in material development and application, giving special attention to preparation methods, tunning of physiochemical properties, surface and interface chemistry, structural porosity, assemblies integration for fabrication of devices, and their relationship with overall efficiency. It offers a valuable reference guide for environmental and materials scientists, engineers, and policymakers working towards environmental sustainability.

This book brings together insights for cancer management from emerging sophisticated information and communication technologies such as artificial intelligence, data science, and big data analytics. It focuses on targeted disease treatment using big data analytics, providing information about targeted treatment in oncology, challenges and application of big data in cancer therapy. Featured topics include: Recent developments in the fields of artificial intelligence, machine learning, medical imaging, personalized medicine, computing and data analytics for improved patient care. Description of the application of big data with AI to discover new targeting points for cancer treatment. Summary of several risk assessments in the field of oncology using big data. Focus on prediction of doses in oncology using big data We are in the era of large-scale science. In oncology there is a huge number of data sets grouping information on cancer genomes, transcriptomes, clinical data, and more. The challenge of big data in cancer is to integrate all this diversity of data collected into a unique platform that can be analyzed, leading to the generation of readable files. The possibility of harnessing information from all the accumulated data leads to an improvement in cancer patient treatment and outcome. Solving the big data problem in oncology has multiple facets. Big data in Oncology: Impact, Challenges, and Risk Assessment brings together insights from emerging sophisticated information and communication technologies such as artificial intelligence, data science, and big data analytics for cancer management. The book is written for academics, research scholars, health care professionals, hospital management, pharmaceutical chemist, biomedical industry, software engineers and IT professionals.

This reference text discusses recent advances in the field of nanotechnology with applications in the fields of electronics sector, agriculture, health services, smart cities, food industry, and energy sector in a comprehensive manner. The text begins by discussing important concepts including bio nanotechnology, nano electronics, nano devices, nano medicine, and nano memories. It then comprehensively covers applications of nanotechnology in different areas including healthcare, energy sector, environment, security and defense, agriculture sector, food industry, automotive sector, smart cities, and Internet of Things (IoT). Aimed at senior undergraduate, graduate students and professionals in the fields of electrical engineering, electronics engineering, nanoscience and nanotechnology, this text: Discusses nano image sensors useful for imaging in medical and for security applications. Covers advances in the field of nanotechnology with their applications. It covers important concepts including neuro simulators, nano medicine, and nano materials. Covers applications of nanotechnology in diverse fields including health sector, agriculture, energy sector, and electronics.

Machine learning approaches has the capability to learn and adapt to the constantly evolving demands of large Internet-of-energy (IoE) network. The focus of this book is on using the machine learning approaches to present various solutions for IoE network in smart cities to solve various research gaps such as demand response management, resource management and effective utilization of the underlying ICT network. It provides in-depth knowledge to build the technical understanding for the reader to pursue various research problems in this field. Moreover, the example problems in smart cities and their solutions using machine learning are provided as relatable to the real-life scenarios. Aimed at Graduate Students, Researchers in Computer Science, Electrical Engineering, Telecommunication Engineering, Internet of Things, Machine Learning, Green computing, Smart Grid, this book: Covers all aspects of Internet of Energy (IoE) and smart cities including research problems and solutions. Points to the solutions provided by machine learning to optimize the grids within a smart city set-up. Discusses relevant IoE design principles and architecture. Helps to automate various services in smart cities for energy management. Includes case studies to show the effectiveness of the discussed schemes.

Present book covers new paradigms in Blockchain, Big Data and Machine Learning concepts including applications and case studies. It explains dead fusion in realizing the privacy and security of blockchain based data analytic environment. Recent research of security based on big data, blockchain and machine learning has been explained through actual work by practitioners and researchers, including their technical evaluation and comparison with existing technologies. The theoretical background and experimental case studies related to real-time environment are covered as well. Aimed at Senior undergraduate students, researchers and professionals in computer science and engineering and electrical engineering, this book: Converges Blockchain, Big Data and Machine learning in one volume. Connects Blockchain technologies with the data centric applications such Big data and E-Health. Easy to understand examples on how to create your own blockchain supported by case studies of blockchain in different industries. Covers big data analytics examples using R. Includes lllustrative examples in python for blockchain creation.

This book presents intelligent data analysis as a tool to fight against COVID-19 pandemic. The intelligent data analysis includes machine learning, natural language processing, and computer vision applications to teach computers to use big data-based models for pattern recognition, explanation, and prediction. These functions are discussed in detail in the book to recognize (diagnose), predict, and explain (treat) COVID-19 infections, and help manage socio-economic impacts. It also discusses primary warnings and alerts; tracking and prediction; data dashboards; diagnosis and prognosis; treatments and cures; and social control by the use of intelligent data analysis. It provides analysis reports, solutions using real-time data, and solution through web applications details.