Gitanjali R. Shinde – författare

VANET (vehicular ad hoc network) is a subgroup of MANET (mobile ad hoc network). It enables communication among vehicles on the road and between related infrastructures. This book addresses the basic elements of VANET along with components involved in the communication with their functionalities and configurations. It contains numerous examples, case studies, technical descriptions, scenarios, procedures, algorithms, and protocols, and addresses the different services provided by VANET with the help of a scenario showing a network tackling an emergency.

Features:

• Covers all important concepts of VANET for beginners and different road scenarios in VANET

• Covers essential communication protocols in VANET

• Introduces approaches for VANET implementation using simulators

• Provides a classification of messages and a priority-based message forwarding strategy

This book is aimed at undergraduates, postgraduates, industry, researchers, and research scholars in information and communications technology.

VANET (vehicular ad hoc network) is a subgroup of MANET (mobile ad hoc network). It enables communication among vehicles on the road and between related infrastructures. This book addresses the basic elements of VANET along with components involved in the communication with their functionalities and configurations. It contains numerous examples, case studies, technical descriptions, scenarios, procedures, algorithms, and protocols, and addresses the different services provided by VANET with the help of a scenario showing a network tackling an emergency.

Features:

• Covers all important concepts of VANET for beginners and different road scenarios in VANET

• Covers essential communication protocols in VANET

• Introduces approaches for VANET implementation using simulators

• Provides a classification of messages and a priority-based message forwarding strategy

This book is aimed at undergraduates, postgraduates, industry, researchers, and research scholars in information and communications technology.

This book focuses on various authorization and access control techniques, threats and attack modeling, including an overview of the Open Authorization 2.0 (OAuth 2.0) framework along with user-managed access (UMA) and security analysis. Important key concepts are discussed regarding login credentials with restricted access to third parties with a primary account as a resource server. A detailed protocol overview and authorization process, along with security analysis of OAuth 2.0, are also discussed in the book. Case studies of websites with vulnerability issues are included.

FEATURES

This book is for researchers and professionals who are engaged in IT security, auditing and computer engineering.

This book focuses on various authorization and access control techniques, threats and attack modeling, including an overview of the Open Authorization 2.0 (OAuth 2.0) framework along with user-managed access (UMA) and security analysis. Important key concepts are discussed regarding login credentials with restricted access to third parties with a primary account as a resource server. A detailed protocol overview and authorization process, along with security analysis of OAuth 2.0, are also discussed in the book. Case studies of websites with vulnerability issues are included.

FEATURES

This book is for researchers and professionals who are engaged in IT security, auditing and computer engineering.

This book explores the need for a data‑centric AI approach and its application in the multidisciplinary domain, compared to a model‑centric approach. It examines the methodologies for data‑centric approaches, the use of data‑centric approaches in different domains, the need for edge AI and how it differs from cloud‑based AI. It discusses the new category of AI technology, "data‑centric AI" (DCAI), which focuses on comprehending, utilizing, and reaching conclusions from data. By adding machine learning and big data analytics tools, data‑centric AI modifies this by enabling it to learn from data rather than depending on algorithms. It can therefore make wiser choices and deliver more precise outcomes. Additionally, it has the potential to be significantly more scalable than conventional AI methods.

• Includes a collection of case studies with experimentation results to adhere to the practical approaches

• Examines challenges in dataset generation, synthetic datasets, analysis, and prediction algorithms in stochastic ways

• Discusses methodologies to achieve accurate results by improving the quality of data

• Comprises cases in healthcare and agriculture with implementation and impact of quality data in building AI applications

This book explores the need for a data‑centric AI approach and its application in the multidisciplinary domain, compared to a model‑centric approach. It examines the methodologies for data‑centric approaches, the use of data‑centric approaches in different domains, the need for edge AI and how it differs from cloud‑based AI. It discusses the new category of AI technology, "data‑centric AI" (DCAI), which focuses on comprehending, utilizing, and reaching conclusions from data. By adding machine learning and big data analytics tools, data‑centric AI modifies this by enabling it to learn from data rather than depending on algorithms. It can therefore make wiser choices and deliver more precise outcomes. Additionally, it has the potential to be significantly more scalable than conventional AI methods.

• Includes a collection of case studies with experimentation results to adhere to the practical approaches

• Examines challenges in dataset generation, synthetic datasets, analysis, and prediction algorithms in stochastic ways

• Discusses methodologies to achieve accurate results by improving the quality of data

• Comprises cases in healthcare and agriculture with implementation and impact of quality data in building AI applications

This book covers all small details about Underwater Sensor Networks (UWSN). Researchers can use this book as a prerequisite before starting any research on underwater networks or underwater applications. This book covers the introduction, challenges, different architectural models for UWSN, various attacks on UWSN, underwater applications, and networking layers. The target audience includes professors and students in engineering, and researchers and engineers working on marine applications. In academic level, the book is helpful for students having Networking and Information Security as elective subject and doing projects in Wireless Networks. It is also helpful for spostgraduates and Ph.D. researchers to learn basics of Underwater Sensor Networks.

This book extends the work from introduction of ubiquitous computing, to the Internet of things to security and to privacy aspects of ubiquitous computing. The uniqueness of this book is the combination of important fields like the Internet of things and ubiquitous computing. It assumes that the readers’ goal is to achieve a complete understanding of IoT, smart computing, security issues, challenges and possible solutions. It is not oriented towards any specific use cases and security issues; privacy threats in ubiquitous computing problems are discussed across various domains. This book is motivating to address privacy threats in new inventions for a wide range of stakeholders like layman to educated users, villages to metros and national to global levels. This book contains numerous examples, case studies, technical descriptions, scenarios, procedures, algorithms and protocols. The main endeavour of this book is threat analysis and activity modelling of attacks in order to give anactual view of the ubiquitous computing applications. The unique approach will help readers for a better understanding.

This book presents cognitive modeling along with the new paradigm machine thinking to enhance existing AI power and address its current limitations. This book provides overview of natural and artificial intelligence along with the computing models used currently. The need of advancing the current models is presented with suitable examples. The business case studies presented in different domains provide possible use of augmented intelligence with the proposed machine thinking paradigm. This book is targeted at academicians, researchers, students, professionals who belong to disciplines which involves intelligent computing and modelling human thinking. It provides possible multidisciplinary research directions including social psychology, artificial intelligence, HCI, cognition for applications in various domains.

This book discusses the best research roadmaps, strategies, and challenges in data-centric approach of artificial intelligence (AI) in various domains. It presents comparative studies of model-centric and data-centric AI. It also highlights different phases in data-centric approach and data-centric principles. The book presents prominent use cases of data-centric AI. It serves as a reference guide for researchers and practitioners in academia and industry.