This handbook is organized under three major parts. The first part of this handbook deals with multimedia security for emerging applications. The chapters include basic concepts of multimedia tools and applications, biological and behavioral biometrics, effective multimedia encryption and secure watermarking techniques for emerging applications, an adaptive face identification approach for android mobile devices, and multimedia using chaotic and perceptual hashing function. The second part of this handbook focuses on multimedia processing for various potential applications. The chapter includes a detail survey of image processing based automated glaucoma detection techniques and role of de-noising, recent study of dictionary learning based image reconstruction techniques for analyzing the big medical data, brief introduction of quantum image processing and it applications, a segmentation-less efficient Alzheimer detection approach, object recognition, image enhancements and de-noising techniques for emerging applications, improved performance of image compression approach, and automated detection of eye related diseases using digital image processing. The third part of this handbook introduces multimedia applications. The chapter includes the extensive survey on the role of multimedia in medicine and multimedia forensics classification, a finger based authentication system for e-health security, analysis of recently developed deep learning techniques for emotion and activity recognition. Further, the book introduce a case study on change of ECG according to time for user identification, role of multimedia in big data, cloud computing, the Internet of things (IoT) and blockchain environment in detail for real life applications. This handbook targets researchers, policy makers, programmers and industry professionals in creating new knowledge for developing efficient techniques/framework for multimedia applications. Advanced level students studying computer science, specifically security and multimedia will find this book useful as a reference.

This book constitutes the refereed proceedings of the 10th International Conference on Applications and Techniques in Information Security, ATIS 2019, held in Tamil Nadul, India, in November 2019. The 22 full papers and 2 short papers presented in the volume were carefully reviewed and selected from 50 submissions. The papers are organized in the following topical sections: information security; network security; intrusion detection system; authentication and key management system; security centric applications.

SUPERVISED and UNSUPERVISED DATA ENGINEERING for MULTIMEDIA DATA Explore the cutting-edge realms of data engineering in multimedia with Supervised and Unsupervised Data Engineering for Multimedia Data, where expert contributors delve into innovative methodologies, offering invaluable insights to empower both novices and seasoned professionals in mastering the art of manipulating multimedia data with precision and efficiency. Supervised and Unsupervised Data Engineering for Multimedia Data presents a groundbreaking exploration into the intricacies of handling multimedia data through the lenses of both supervised and unsupervised data engineering. Authored by a team of accomplished experts in the field, this comprehensive volume serves as a go-to resource for data scientists, computer scientists, and researchers seeking a profound understanding of cutting-edge methodologies. The book seamlessly integrates theoretical foundations with practical applications, offering a cohesive framework for navigating the complexities of multimedia data. Readers will delve into a spectrum of topics, including artificial intelligence, machine learning, and data analysis, all tailored to the challenges and opportunities presented by multimedia datasets. From foundational principles to advanced techniques, each chapter provides valuable insights, making this book an essential guide for academia and industry professionals alike. Whether you’re a seasoned practitioner or a newcomer to the field, Supervised and Unsupervised Data Engineering for Multimedia Data illuminates the path toward mastery in manipulating and extracting meaningful insights from multimedia data in the modern age.

Because it makes the distribution and transmission of digital information much easier and more cost effective, multimedia has emerged as a top resource in the modern era. In spite of the opportunities that multimedia creates for businesses and companies, information sharing remains vulnerable to cyber attacks and hacking due to the open channels in which this data is being transmitted. Protecting the authenticity and confidentiality of information is a top priority for all professional fields that currently use multimedia practices for distributing digital data. The Handbook of Research on Multimedia Cyber Security provides emerging research exploring the theoretical and practical aspects of current security practices and techniques within multimedia information and assessing modern challenges. Featuring coverage on a broad range of topics such as cryptographic protocols, feature extraction, and chaotic systems, this book is ideally designed for scientists, researchers, developers, security analysts, network administrators, scholars, IT professionals, educators, and students seeking current research on developing strategies in multimedia security.

This book will highlight cutting-edge research with a particular emphasis on interdisciplinary approaches, novel techniques, and solutions to provide digital image security for applications in diverse areas. It further discusses important topics such as biometric imaging, big data security and privacy in healthcare, security and privacy in the internet of things, and security in cloud-based image processing. This book Presents new ideas, approaches, theories, and practices with a focus on digital image security and privacy solutions for real-world applications. Discusses security in cloud-based image processing for smart city applications. Provides an overview of innovative security techniques that are being developed to ensure the guaranteed authenticity of transmitted, shared, or stored digital images. Highlights approaches such as watermarking, blockchain, and hashing. to secure digital images in artificial intelligence, machine learning, cloud computing, and temper detection environments. Explains important topics such as biometric imaging, blockchain for digital data security, and protection systems against personal identity theft. It will serve as an ideal reference text for senior undergraduate, graduate students, academic researchers, and professionals in the fields including electrical engineering, electronics, communications engineering, and computer engineering.

This book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2022) held at Institute of Engineering & Management, Kolkata, India, during February 23–25, 2022. The book is organized in three volumes and includes high-quality research work by academicians and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers and case studies related to all the areas of data mining, machine learning, Internet of Things (IoT) and information security.

Social media sites are constantly evolving with huge amounts of scattered data or big data, which makes it difficult for researchers to trace the information flow. It is a daunting task to extract a useful piece of information from the vast unstructured big data; the disorganized structure of social media contains data in various forms such as text and videos as well as huge real-time data on which traditional analytical methods like statistical approaches fail miserably. Due to this, there is a need for efficient data mining techniques that can overcome the shortcomings of the traditional approaches. Data Mining Approaches for Big Data and Sentiment Analysis in Social Media encourages researchers to explore the key concepts of data mining, such as how they can be utilized on online social media platforms, and provides advances on data mining for big data and sentiment analysis in online social media, as well as future research directions. Covering a range of concepts from machine learning methods to data mining for big data analytics, this book is ideal for graduate students, academicians, faculty members, scientists, researchers, data analysts, social media analysts, managers, and software developers who are seeking to learn and carry out research in the area of data mining for big data and sentiment.

The purpose of this edited book is to present and showcase the basic fundamentals, applications, and integration of both IoT and Blockchain. The trend of applying Blockchain to IoT is rapidly growing because it helps to overcome various challenges faced by IoT, from smart manufacturing to unmanned aerial vehicles. Thise book aims to showcase the basics of both IoT and Blockchain as well as the integration and challenges for existing practitioners. Thise book initiates conversations among technologists, engineers, scientists, and clinicians to synergize their efforts in producing low-cost, high-performance, highly efficient, deployable IoT systems. Thise book is theory-based and is useful for engineers from various disciplines, including industrial engineering, computer science, electronics, telecommunications, electrical, agricultural, and cybersecurity, along with researchers, professionals, and students.

Machine learning, Internet of Things (IoT) and data analytics are new and fresh technologies that are being increasingly adopted in the field of medicine. This book positions itself at the forefront of this movement, exploring the beneficial applications of these new technologies and how they are gradually creating a smart healthcare system. This book details the various ways in which machine learning, data analytics and IoT solutions are instrumental in disease prediction in smart healthcare. For example, wearable sensors further help doctors and healthcare managers to monitor patients remotely and collect their health parameters in real-time, which can then be used to create datasets to develop machine learning models that can aid in the prediction and detection of any susceptible disease. In this way, smart healthcare can provide novel solutions to traditional medical issues. This book is a useful overview for scientists, researchers, practitioners and academics specialising in the field of intelligent healthcare, as well as containing additional appeal as a reference book for undergraduate and graduate students

A smart ecosystem is envisioned to exchange and analyze data across systems, enabling a flexible, faster, and reliable smart ecosystem for high-quality results at reduced costs and little human intervention. This book introduces many innovative approaches and provides solutions to various problems of smart ecosystems designed by employing various techniques/models based on AI, ML, Deep Learning, and the Internet of Things (IoT). The main focus is on intelligent multimedia processing and automated decision-making for various services, real-time data analysis, data security, cost-effective solutions for multimedia applications, smart information processing systems, and smart city planning to name a few. In addition, this book presents some key insights and future directions in the various areas of technology. Throughout the book, many state-of-the-art solutions concerning various applications are proposed to solve the issues and ensure the quality of services (QoS). The authors discuss the limitations of the current techniques used to design a smart ecosystem and highlight some prospective areas of research in the future. The book comprehensively discusses multimedia processing of various forms of data comprising text, images, and audio for the implementation of various solutions. The book is aimed to open many areas of research and thus would present a comprehensive reference for the design of smart ecosystems in various applications.