Deep Learning Approaches to Cloud Security. Группа авторов

who are working in the field of blockchain, cryptography, network security, and security and privacy issues in the Internet of Things (IoT). It will also be useful for faculty members of graduate schools and universities. The book series provides a comprehensive look at the various facets of cloud security: infrastructure, network, services, compliance and users. It will provide real-world case studies to articulate the real and perceived risks and challenges in deploying and managing services in a cloud infrastructure from a security perspective. The book series will serve as a platform for books dealing with security concerns of decentralized applications (DApps) and smart contracts that operate on an open blockchain. The book series will be a comprehensive and up-to-date reference on information security and assurance. Bringing together the knowledge, skills, techniques, and tools required of IT security professionals, it facilitates the up-to-date understanding required to stay one step ahead of evolving threats, standards, and regulations.

       Publishers at Scrivener

      Martin Scrivener ([email protected]) Phillip Carmical ([email protected])

      Deep Learning Approaches to Cloud Security

      Edited by

       Pramod Singh Rathore

       Vishal Dutt

       Rashmi Agrawal

       Satya Murthy Sasubilli

      and

       Srinivasa Rao Swarna

      This edition first published 2022 by John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA

      © 2022 Scrivener Publishing LLC

      For more information about Scrivener publications please visit www.scrivenerpublishing.com.

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       Library of Congress Cataloging-in-Publication Data

      ISBN 9781119760528

      Cover image: Stockvault.com

      Cover design by Russell Richardson

      Set in size of 11pt and Minion Pro by Manila Typesetting Company, Makati, Philippines

      Printed in the USA

      10 9 8 7 6 5 4 3 2 1

      Foreword

      This is Dr. Abhishek Kumar, Assistant Professor in Chitkara University, Himachal Pradesh. I have been involved in the research for more than 8 years with the authors of this book. This book is about a solution to these more intuitive problems. This solution is to allow computers to learn from experience and understand the world in terms of a hierarchy of concepts, with each concept defined through its relation to simpler concepts.

      This book is about how Deep Learning is the fastest growing field in computer science. Deep Learning algorithms and techniques are found to be useful in different areas like Automatic Machine Translation, Automatic Handwriting Generation, Visual Recognition, Fraud Detection, Detecting Developmental Delay in Children. However, applying Deep Learning techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. This book provides state of the art approaches of Deep Learning in these areas. It includes areas of detection, prediction, as well as future framework development, building service systems and analytical aspects. In all these topics, approaches of Deep Learning such as artificial neural networks, fuzzy logic, genetic algorithm and hybrid mechanisms are used. This book is intended for dealing with modeling and performance prediction of the efficient cloud security systems thereby bringing newer dimension.

This book shall help clarify understanding of certain key mechanism of technology helpful in realizing such system. Enables processing of very large dataset help with precise and comprehensive forecast of risk and delivers recommended action that improve outcome for consumer. It is a novel application domain of deep learning that is of prime importance to human civilization as a whole. This would be helpful for both professionals and students, with state-of-the art knowledge on the frontiers in information assurance. This book is a good step in that direction.

       Dr. Abhishek Kumar

       Assistant Professor

       Abhishek Kumar || Assistant Professor, PhD, Senior Member (IEEE)

       Chitkara University Research and Innovation Network (CURIN) Chitkara University, India

      Preface

      This book is organized into fifteen chapters. Chapter 1 discusses the prevailing Biometric modalities, classification, and their working. It goes on to discuss the various approaches used for Facial Biometric Identification such as feature selection, extraction, face marking, and the nearest neighbor approach.