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.

Global supply chains are becoming more customer-centric and sustainable thanks to next-generation logistics management technologies. Automating logistics procedures greatly increases the productivity and efficiency of the workflow. There is a need, however, to create flexible and dynamic relationships among numerous stakeholders and the transparency and traceability of the supply chain. The digitalization of the supply chain process has improved these relationships and transparency; however, it has also created opportunities for cybercriminals to attack the logistics industry. Cybersecurity Measures for Logistics Industry Framework discusses the environment of the logistics industry in the context of new technologies and cybersecurity measures. Covering topics such as AI applications, inventory management, and sustainable computing, this premier reference source is an excellent resource for business leaders, IT managers, security experts, students and educators of higher education, librarians, researchers, and academicians.

The need for sustainable sources of energy has become more prevalent in an effort to conserve natural resources, as well as optimize the performance of wireless networks in daily life. Renewable sources of energy also help to cut costs while still providing a reliable power sources. Biologically-Inspired Energy Harvesting through Wireless Sensor Technologies highlights emerging research in the areas of sustainable energy management and transmission technologies. Featuring technological advancements in green technology, energy harvesting, sustainability, networking, and autonomic computing, as well as bio-inspired algorithms and solutions utilized in energy management, this publication is an essential reference source for researchers, academicians, and students interested in renewable or sustained energy in wireless networks.

The healthcare industry is starting to adopt digital twins to improve personalized medicine, healthcare organization performance, and new medicine and devices. These digital twins can create useful models based on information from wearable devices, omics, and patient records to connect the dots across processes that span patients, doctors, and healthcare organizations as well as drug and device manufacturers. Digital twins are digital representations of human physiology built on computer models. The use of digital twins in healthcare is revolutionizing clinical processes and hospital management by enhancing medical care with digital tracking and advancing modelling of the human body. These tools are of great help to researchers in studying diseases, new drugs, and medical devices. Digital Twins and Healthcare: Trends, Techniques, and Challenges facilitates the advancement and knowledge dissemination in methodologies and applications of digital twins in the healthcare and medicine fields. This book raises interest and awareness of the uses of digital twins in healthcare in the research community. Covering topics such as deep neural network, edge computing, and transfer learning method, this premier reference source is an essential resource for hospital administrators, pharmacists, medical professionals, IT consultants, students and educators of higher education, librarians, and researchers.

The digital divide, caused by several factors such as poverty and slow communication technologies, has offset the progression of many developing countries. However, with rapid changes in technology, a better collaboration among communities and governance based on the latest research in ICT and technology has begun to emerge. Employing Recent Technologies for Improved Digital Governance is an essential reference source that provides research on recent advances in the development, application, and impact of technologies for the initiative of digital governance. The book has a dual objective with the first objective being to encourage more research in deploying recent trends in the internet for deploying a collaborative digital governance. The second objective is to explore new possibilities using internet of things (IoT) and cloud/fog-based solutions for creating a collaboration between the governance and IT infrastructure. Featuring research on topics such as intelligent systems, social engineering, and cybersecurity, this book is ideally designed for policymakers, government officials, ICT specialists, researchers, academicians, industry professionals, and students.

The recent advancements in the machine learning paradigm have various applications, however, it has shown significant results in the field of medical data analysis. The results are highly accurate and are comparable to human experts. The various research has proved the high accuracy of deep learning algorithms and has become a standard choice for analysing medical data, especially medical images, video, and electronic health records. Deep learning methods applied to electronic health records are contributing to understanding the evolution of chronic diseases and predicting the risk of developing those diseases. Researchers in industry, hospitals, and academia have published hundreds of scientific contributions in this area during a pandemic. This book is an ideal and relevant source of content for data science and healthcare professionals who want to delve into complex deep learning algorithms, calibrate models, and improve the predictions of the trained model on medical imaging. Primary audiences for this book are professionals and researchers in the fields of data science, machine learning, deep learning, and AI. Also academicians, healthcare professionals, or anyone who may have a keen interest in how the machine and deep learning algorithms are helping in the identification of solutions to medical sensor/image data analysis, event detection, segmentation, and abnormality detection, object/lesion classification, organ/region/landmark localization, object/lesion detection, organ/substructure segmentation, lesion segmentation, and medical image registration. The variety of readers in the fields of government, consulting, healthcare professionals, as well as the readers from all the social strata, can also be benefited from this book to improve understanding of the cutting-edge theory, technologies, methodologies, and applications of deep Learning algorithms for medical care.

Software development and information systems design have a unique relationship, but are often discussed and studied independently. However, meticulous software development is vital for the success of an information system. Software Development Techniques for Constructive Information Systems Design focuses the aspects of information systems and software development as a merging process. This reference source pays special attention to the emerging research, trends, and experiences in this area which is bound to enhance the reader s understanding of the growing and ever-adapting field. Academics, researchers, students, and working professionals in this field will benefit from this publication s unique perspective.

E-governance is an application of IT; holding uses for the delivery of Government services, information exchange between Government to public, e-business, and various. However, the aim of cybersecurity is to provide security from cyber-attacks from the view of emerging technology is used by hackers. Hence, it is important to provide fast protection application software and structure. In this scenario, the government may be focused to provide capable Internet carefully without the risk of fraud. These days the study deliberates about the issue of the world while technology is helping and fruitful on each step of life like e-Governance applications. Though, has been limited study has been done by a previous study on protocols of cybersecurity for e-Governance.

It is also essential to study the success of technology use in some of the advanced nations in the Asian region that promote a smarter and well-advanced community. A smarter community in these regions can only be materialized by adopting the latest trends in technology to improve quality of life. Some of these regions need a great emphasis on technology adoption for women empowerment and safety, promoting better health with telemedicine facilities, environment, and disaster prevention with IoT technologies, water treatment and sanitation, and addressing food scarcity issues with smarter precision agriculture. Ultimately, there needs to be more research focused on a smarter and secured community in the Asian region in terms of cultural and socioeconomic factors and technology advancements. ICT Solutions for Improving Smart Communities in Asia explores new possibilities using digital solutions and technologies to create collaborative and smarter communities for advancement in agriculture, the health sector, education centers, human resources, and administrative domains, as well as other areas to improve the overall living standards of people at the community level. This book will cover two main areas: the need for technology development in developing nations, mainly focusing on Asia, and the adoption of some of the advanced regions in Asia as role models for the less developed SAARC regions explicitly. This book is ideally intended for researchers, academicians, IT specialists, regional developers, government officials, practitioners, academicians, and students.

In the era of Industry 4.0, the world is increasingly becoming smarter as everything from mobile phones to cars to TVs connects with unique addresses and communication mechanisms. However, in order to enable the smart world to be sustainable, ICT must embark into energy efficient paradigms. Green ICT is a moving factor contributing towards energy efficiency by reducing energy utilization through software or hardware procedures. Role of IoT in Green Energy Systems presents updated research trends in green technology and the latest product and application developments towards green energy. Covering topics that include energy conservation and harvesting, renewable energy, and green and underwater internet of things, this essential reference book creates further awareness of smart energy and critically examines the contributions of ICT towards green technologies. IT specialists, researchers, academicians, and students in the area of energy harvesting and energy management, and/or those working towards green energy technologies, wireless sensor networks, and smart applications will find this monograph beneficial in their studies.

The recent advancement of industrial computerization has significantly helped in resolving the challenges associated with the conventional industrial systems. The industry 4.0 quality standards demand smart and intelligent solutions to revolutionize the industrial applications. Despite, a wide range of available industrial solutions, still the precision, accuracy and speed are a matter of interest to scientists to device novel solutions. In addition, the IoT technologies, though, have gained an inspiration in industrial applications, yet, the time and resource complexity of industrial sensors require intelligent management and monitoring of sensors' data. The integration of machine intelligence and IoT technologies can greatly help in devising cutting edge solutions to very recent issues of industrial applications. Machine intelligence is the most appropriate set of techniques for constructing prediction models due to its capability in handling large-scale and complex datasets. Machine intelligent solution can effectively help the industrial stakeholders in automatic detection of faults, early prediction of errors and risks, tracking industrial shipments through intelligent sensors, health industry risk mitigation employing IoT and machine intelligence, disaster management, and many more. The objectives include: Assessment of limitations of industrial systems, challenges and solutions; Empowerment of industrial systems with machine intelligence to mitigate the risks; Smart safety measures towards industrial systems; and Presentation of recent intelligent systems for a wide range of industrials applications.

This book presents a detailed exploration of adaption and implementation, as well as a 360-degree view spectrum of blockchain technologies in real-world business applications. Blockchain is gaining momentum in all sectors. This book offers a collection of protocol standards, issues, security improvements, applicability, features, and types of cryptocurrency in processing and through 5G technology. The book covers the evolution of blockchain from fundamental theories to present forms. It offers diversified business applications with usable case studies and provides successful implementations in cloud/edge computing, smart city, and IoT. The book emphasizes the advances and cutting-edge technologies along with the different tools and platforms. The primary audience for this book includes industry experts, researchers, graduates and under graduates, practitioners, and business managers who are engaged in blockchain and IoT-related technologies.

Big data is a well-trafficked subject in recent IT discourse and does not lack for current research. In fact, there is such a surfeit of material related to big data-and so much of it of questionably reliability, thanks to the high-gloss efforts of savvy tech-marketing gurus-that it can, at times, be difficult for a serious academician to navigate. The Handbook of Research on Trends and Future Directions in Big Data and Web Intelligence cuts through the haze of glitz and pomp surrounding big data and offers a simple, straightforward reference-source of practical academic utility. Covering such topics as cloud computing, parallel computing, natural language processing, and personalized medicine, this volume presents an overview of current research, insight into recent advances, and gaps in the literature indicative of opportunities for future inquiry and is targeted toward a broad, interdisciplinary audience of students, academics, researchers, and professionals in fields of IT, networking, and data-analytics.

Cyber Security Applications for Industry 4.0 (CSAI 4.0) provides integrated features of various disciplines in Computer Science, Mechanical, Electrical, and Electronics Engineering which are defined to be Smart systems. It is paramount that Cyber-Physical Systems (CPS) provide accurate, real-time monitoring and control for smart applications and services. With better access to information from real-time manufacturing systems in industrial sectors, the CPS aim to increase the overall equipment effectiveness, reduce costs, and improve efficiency. Industry 4.0 technologies are already enabling numerous applications in a variety of industries. Nonetheless, legacy systems and inherent vulnerabilities in an organization's technology, including limited security mechanisms and logs, make the move to smart systems particularly challenging. Features: Proposes a conceptual framework for Industry 4.0-based Cyber Security Applications concerning the implementation aspect Creates new business models for Industrialists on Control Systems and provides productive workforce transformation Outlines the potential development and organization of Data Protection based on strategies of cybersecurity features and planning to work in the new area of Industry 4.0 Addresses the protection of plants from the frost and insects, automatic hydroponic irrigation techniques, smart industrial farming and crop management in agriculture relating to data security initiatives The book is primarily aimed at industry professionals, academicians, and researchers for a better understanding of the secure data transition between the Industry 4.0 enabled connected systems and their limitations

Addresses the knowledge for emerging multidisciplinary research Explores basic and high level concepts and serves as a manual for industry Presents security and privacy issues through IoT ecosystems and its implications to the real-world Explains concepts of IoT related technologies, trends, and future directions related to information security Examines privacy issues and challenges related to data-intensive technologies in IoT

The advanced AI techniques are essential for resolving various problematic aspects emerging in the field of bioinformatics. This book covers the recent approaches in artificial intelligence and machine learning methods and their applications in Genome and Gene editing, cancer drug discovery classification, and the protein folding algorithms among others. Deep learning, which is widely used in image processing, is also applicable in bioinformatics as one of the most popular artificial intelligence approaches. The wide range of applications discussed in this book are an indispensable resource for computer scientists, engineers, biologists, mathematicians, physicians, and medical informaticists. Features: Focusses on the cross-disciplinary relation between computer science and biology and the role of machine learning methods in resolving complex problems in bioinformatics Provides a comprehensive and balanced blend of topics and applications using various advanced algorithms Presents cutting-edge research methodologies in the area of AI methods when applied to bioinformatics and innovative solutions Discusses the AI/ML techniques, their use, and their potential for use in common and future bioinformatics applications Includes recent achievements in AI and bioinformatics contributed by a global team of researchers

The study of Wireless Sensor Networks (WSN) is a continually growing, as these networks have the advantage of easy deployment for a number of different applications. Wireless Sensor Networks and Energy Efficiency: Protocols, Routing and Management focuses on wireless sensor networks and their operation, covering topics including routing, energy efficiency and management. Containing 27 chapters authored by a group of internationally experienced professionals and researchers in the fields of computer science, communication, and networking, this book discusses critical issues in wireless sensor network research including MAC, Routing Protocols, TCP, performance and traffic management, time synchronization, and security.

This book constitutes the refereed proceedings of the 4th International Conference on Computing Science, Communication and Security, COMS2 2023, held in Gandhinagar, India, during February 6–7, 2023.  The 20 full papers included in this book were carefully reviewed and selected from 190 submissions. They were organized in topical sections on artificial intelligence and machine learning; networking and communications.

The evolution of mechanical properties and its characterization is important to the weld quality whose further analysis requires mechanical property and microstructure correlation. Present book addresses the basic understanding of the Friction Stir Welding (FSW) process that includes effect of various process parameters on the quality of welded joints. It discusses about various problems related to the welding of dissimilar aluminium alloys including influence of FSW process parameters on the microstructure and mechanical properties of such alloys. As a case study, effect of important process parameters on joint quality of dissimilar aluminium alloys is included.

There are a lot of e-business security concerns. Knowing about e-business security issues will likely help overcome them. Keep in mind, companies that have control over their e-business are likely to prosper most. In other words, setting up and maintaining a secure e-business is essential and important to business growth. This book covers state-of-the art practices in e-business security, including privacy, trust, security of transactions, big data, cloud computing, social network, and distributed systems.

This book comprises theoretical foundations to deep learning, machine learning and computing system, deep learning algorithms, and various deep learning applications. The book discusses significant issues relating to deep learning in data analytics. Further in-depth reading can be done from the detailed bibliography presented at the end of each chapter. Besides, this book's material includes concepts, algorithms, figures, graphs, and tables in guiding researchers through deep learning in data science and its applications for society. Deep learning approaches prevent loss of information and hence enhance the performance of data analysis and learning techniques. It brings up many research issues in the industry and research community to capture and access data effectively. The book provides the conceptual basis of deep learning required to achieve in-depth knowledge in computer and data science. It has been done to make the book more flexible and to stimulate further interest in topics. All these help researchers motivate towards learning and implementing the concepts in real-life applications.