SK Hafizul Islam – författare

Blockchain Technology for Emerging Applications: A Comprehensive Approach explores recent theories and applications of the execution of blockchain technology. Chapters look at a wide range of application areas, including healthcare, digital physical frameworks, web of-things, smart transportation frameworks, interruption identification frameworks, ballot-casting, architecture, smart urban communities, and digital rights administration. The book addresses the engineering, plan objectives, difficulties, constraints, and potential answers for blockchain-based frameworks.

It also looks at blockchain-based design perspectives of these intelligent architectures for evaluating and interpreting real-world trends. Chapters expand on different models which have shown considerable success in dealing with an extensive range of applications, including their ability to extract complex hidden features and learn efficient representation in unsupervised environments for blockchain security pattern analysis.

Introduces the basic architecture and taxonomy of blockchain technology Surveys the most recent developments and challenges in blockchain-enabled technology for various application domains with fundamental and technical depth Investigates how to devise secure and reliable applications and blockchain-enabled decentralized secure solutions using blockchain technology

With the rapidly advancing fields of Data Analytics and Computational Statistics, it’s important to keep up with current trends, methodologies, and applications. This book investigates the role of data mining in computational statistics for machine learning. It offers applications that can be used in various domains and examines the role of transformation functions in optimizing problem statements. Data Analytics, Computational Statistics, and Operations Research for Engineers: Methodologies and Applications presents applications of computationally intensive methods, inference techniques, and survival analysis models. It discusses how data mining extracts information and how machine learning improves the computational model based on the new information. Those interested in this reference work will include students, professionals, and researchers working in the areas of data mining, computational statistics, operations research, and machine learning.

With the rapidly advancing fields of Data Analytics and Computational Statistics, it’s important to keep up with current trends, methodologies, and applications. This book investigates the role of data mining in computational statistics for machine learning. It offers applications that can be used in various domains and examines the role of transformation functions in optimizing problem statements. Data Analytics, Computational Statistics, and Operations Research for Engineers: Methodologies and Applications presents applications of computationally intensive methods, inference techniques, and survival analysis models. It discusses how data mining extracts information and how machine learning improves the computational model based on the new information. Those interested in this reference work will include students, professionals, and researchers working in the areas of data mining, computational statistics, operations research, and machine learning.

IoT Security: Fundamentals and Key Enabling Technologies explores the complex interactions between Internet of Things (IoT) and the pressing need for effective cyber security solutions. Diving into real-world case studies to provide insights into implementing efficient security measures that safeguard against online dangers, this book comprehensively analyzes the challenges and possibilities presented by intelligent technologies fueling transformational change, emphasizing the crucial role cybersecurity plays in defending networks, data, and user privacy in an increasingly interconnected digital ecosystem.Coverage includes cryptographic methods, communication networks, device identity and access, data governance and privacy, as well as regulatory frameworks and standards for IoT security. Computer science researchers and engineers will benefit from this compilation of cutting-edge research and practical case studies, learning how to minimize risks for IoT and intelligent technologies.Covers emerging application areas in IoT and possible applications of cybersecurity solutionsPresents cutting-edge blockchain-enabled applications for smart cities, cyber-physical systems, cloud computing, intelligent transportation systems, and network securityOffers both theoretical insights and applications of blockchain, edge computing, machine learning/AI, penetration testing, and collaborative security approaches

QUANTUM BLOCKCHAINWhile addressing the security challenges and threats in blockchain, this book is also an introduction to quantum cryptography for engineering researchers and students in the realm of information security.Quantum cryptography is the science of exploiting quantum mechanical properties to perform cryptographic tasks. By utilizing unique quantum features of nature, quantum cryptography methods offer everlasting security.The applicability of quantum cryptography is explored in this book. It describes the state-of-the-art of quantum blockchain techniques and sketches how they can be implemented in standard communication infrastructure. Highlighting a wide range of topics such as quantum cryptography, quantum blockchain, post-quantum blockchain, and quantum blockchain in Industry 4.0, this book also provides the future research directions of quantum blockchain in terms of quantum resilience, data management, privacy issues, sustainability, scalability, and quantum blockchain interoperability. Above all, it explains the mathematical ideas that underpin the methods of post-quantum cryptography security.Readers will find in this book a comprehensiveness of the subject including: The key principles of quantum computation that solve the factoring issue.A discussion of a variety of potential post-quantum public-key encryption and digital signature techniques.Explanations of quantum blockchain in cybersecurity, healthcare, and Industry 4.0.Audience The book is for security analysts, data scientists, vulnerability analysts, professionals, academicians, researchers, industrialists, and students working in the fields of (quantum) blockchain, cybersecurity, cryptography, and artificial intelligence with regard to smart cities and Internet of Things.

This book is a comprehensive, hands-on guide to the basics of data mining and machine learning with a special emphasis on supervised and unsupervised learning methods. The book is useful for professionals, students studying data mining and machine learning, and researchers in supervised and unsupervised learning techniques.

This book is a comprehensive, hands-on guide to the basics of data mining and machine learning with a special emphasis on supervised and unsupervised learning methods. The book lays stress on the new ways of thinking needed to master in machine learning based on the Python, R, and Java programming platforms. This book first provides an understanding of data mining, machine learning and their applications, giving special attention to classification and clustering techniques. The authors offer a discussion on data mining and machine learning techniques with case studies and examples. The book also describes the hands-on coding examples of some well-known supervised and unsupervised learning techniques using three different and popular coding platforms: R, Python, and Java. This book explains some of the most popular classification techniques (K-NN, Naïve Bayes, Decision tree, Random forest, Support vector machine etc,) along with the basic description of artificial neural network and deep neural network. The book is useful for professionals, students studying data mining and machine learning, and researchers in supervised and unsupervised learning techniques.