Sangeeta Rani – författare

This edited book is a compilation of scholarly articles on the latest developments in the field of AI, Blockchain, and ML/DL in cloud security. This book is designed for security and risk assessment professionals, and to help undergraduate, postgraduate students, research scholars, academicians, and technology professionals who are interested in learning practical approaches to cloud security. It covers practical strategies for assessing the security and privacy of cloud infrastructure and applications and shows how to make cloud infrastructure secure to combat threats and attacks, and prevent data breaches. The chapters are designed with a granular framework, starting with the security concepts, followed by hands-on assessment techniques based on real-world studies. Readers will gain detailed information on cloud computing security that—until now—has been difficult to access.

This book:

• Covers topics such as AI, Blockchain, and ML/DL in cloud security.

• Presents several case studies revealing how threat actors abuse and exploit cloud environments to spread threats.

• Explains the privacy aspects you need to consider in the cloud, including how they compare with aspects considered in traditional computing models.

• Examines security delivered as a service—a different facet of cloud security.

This edited book is a compilation of scholarly articles on the latest developments in the field of AI, Blockchain, and ML/DL in cloud security. This book is designed for security and risk assessment professionals, and to help undergraduate, postgraduate students, research scholars, academicians, and technology professionals who are interested in learning practical approaches to cloud security. It covers practical strategies for assessing the security and privacy of cloud infrastructure and applications and shows how to make cloud infrastructure secure to combat threats and attacks, and prevent data breaches. The chapters are designed with a granular framework, starting with the security concepts, followed by hands-on assessment techniques based on real-world studies. Readers will gain detailed information on cloud computing security that—until now—has been difficult to access.

This book:

• Covers topics such as AI, Blockchain, and ML/DL in cloud security.

• Presents several case studies revealing how threat actors abuse and exploit cloud environments to spread threats.

• Explains the privacy aspects you need to consider in the cloud, including how they compare with aspects considered in traditional computing models.

• Examines security delivered as a service—a different facet of cloud security.

This book is discussing artificial intelligence-based smart systems for diagnosis and prediction of diseases, artificial intelligence in clinical decision-making, and artificial intelligence tools for clinical and healthcare data. It further highlights the importance of 5G and 6G communication for telemedicine applications and applications of machine learning and deep learning in pandemic epidemiology.

This book:

It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields including computer science and engineering, electronics and communications engineering, and biomedical engineering.

This book is discussing artificial intelligence-based smart systems for diagnosis and prediction of diseases, artificial intelligence in clinical decision-making, and artificial intelligence tools for clinical and healthcare data. It further highlights the importance of 5G and 6G communication for telemedicine applications and applications of machine learning and deep learning in pandemic epidemiology.

This book:

It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields including computer science and engineering, electronics and communications engineering, and biomedical engineering.

There is a need to categorize AI applications, tools, techniques, and algorithms based on their intended use in various design stages. Specifically, there is a need to explore AI techniques that are utilized for things such as design tasks, including but not limited to inspiration, idea and concept generation, concept evaluation, optimization, decision-making, and modeling. This includes things like generating ideas and concepts, evaluating those ideas, optimizing designs, making decisions, and creating models. This handbook brings all of these categories with compatible AI techniques, tools, and algorithms together in one place.

Handbook of AI in Engineering Applications: Tools, Techniques, and Algorithms covers applications of AI in engineering and highlights areas such as future cities, mechanical system analysis, and robotic process automation, and presents the application of AI and the use of computerized systems that aim to simplify and automate the processes of design and construction of civil works. The handbook discusses the design and optimization of mechanical systems and parts, such as engines, gears, and bearings, which can be automated using AI and it explores the performance of robotics and automation systems which can be simulated and analyzed using AI to forecast behavior, spot future issues, and suggest changes. Rounding out this handbook is AI technology automation and how analyzing relevant data can provide a reliable basis for relevant personnel to carry out their work.

This handbook fills the gap between R&D in AI and will benefit all stakeholders including industries, professionals, technologists, academics, research scholars, senior graduate students, government, and public healthcare professionals.

There is a need to categorize AI applications, tools, techniques, and algorithms based on their intended use in various design stages. Specifically, there is a need to explore AI techniques that are utilized for things such as design tasks, including but not limited to inspiration, idea and concept generation, concept evaluation, optimization, decision-making, and modeling. This includes things like generating ideas and concepts, evaluating those ideas, optimizing designs, making decisions, and creating models. This handbook brings all of these categories with compatible AI techniques, tools, and algorithms together in one place.

Handbook of AI in Engineering Applications: Tools, Techniques, and Algorithms covers applications of AI in engineering and highlights areas such as future cities, mechanical system analysis, and robotic process automation, and presents the application of AI and the use of computerized systems that aim to simplify and automate the processes of design and construction of civil works. The handbook discusses the design and optimization of mechanical systems and parts, such as engines, gears, and bearings, which can be automated using AI and it explores the performance of robotics and automation systems which can be simulated and analyzed using AI to forecast behavior, spot future issues, and suggest changes. Rounding out this handbook is AI technology automation and how analyzing relevant data can provide a reliable basis for relevant personnel to carry out their work.

This handbook fills the gap between R&D in AI and will benefit all stakeholders including industries, professionals, technologists, academics, research scholars, senior graduate students, government, and public healthcare professionals.