Название: Future Connected Technologies: Growing Convergence and Security ImplicationsАвтор: Maanak Gupta, Ravi Tomar, Anuj Kumar Yadav, Hanumat Sastry G.
Издательство: CRC Press
Год: 2023
Страниц: 249
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB
The main aim of the book is to familiarize readers with the concepts of convergence of different connected and smart domains that are assisted by Cloud Computing, core technologies behind Cloud Computing, driving factors towards Cloud Computing, and security challenges and proposed solutions in Cloud Computing. The book covers not only the cloud, but also other pertinent topics such as Machine Learning, Deep Learning, IoT and Fog/Edge Computing. The last section of the book mainly focuses on the security aspects of connected technologies. The highpoints of the book is that it reviews the relation and combination of the mentioned topics, which together creates a better understanding about almost every aspect of Cloud Computing & related technologies.
Deep Learning techniques are evolving and implemented in various fields of study. Traditionally, in classification, input data is subjected to the training model and performance measures like accuracy, precision and recall are obtained. Exploration on the reasoning behind the model performance falls under the domain of explainable artificial intelligence. Why can the model classify some items correctly and not the others? Questions like these are categorized under Explainable AI (XAI).
It is comprised of thirteen chapters and each presenting a complete insight into the chosen problem. Chapter 1 discusses the role of Quantum Computing in Cloud Security. Chapter 2 is about providing security solutions to Cloud and Cyber-Physical Systems using Blockchain technology. Chapter 3 discusses a detailed review of access control methods in Cloud computing. Chapter 4 proposes solutions to enablement of smart city initiatives using different security methods.
Chapter 5 is dedicated to discussions regarding knowledge representation using Deep learning methods. Chapter 6 presents Machine learning techniques and their use in healthcare. The chapter mainly emphasizes heart disease prediction.
Chapters 7 and 8 are based on the Edge computing technique, in which first the architecture is presented and later security concepts in Edge computing are discussed. Chapter 9 discusses the application of Data-Analytics in cardiovascular disease prediction. Chapter 10 presents the role of Edge computing in smart agriculture. Chapters 11 and 12 explain the theoretical background regarding Cloud computing, IoT, and Edge computing.
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