Deep Learning Approaches to Cloud Security

Name: Deep Learning Approaches to Cloud Security
Brand: Unknown
SKU: 9781119760528
Price: 451.99 NZD
Availability: InStock

0.0 (0 reviews)

Summary

Deep Learning Approaches to Cloud Security delves into the intersection of cutting-edge artificial intelligence techniques and cloud protection measures. This book explores how deep learning can be utilised to enhance security protocols, ensuring data integrity and safeguarding sensitive information across cloud platforms. It's an essential read for technology enthusiasts seeking to understand the evolving landscape of cloud security.
Read More

Format: Hardback

$451⁹⁹

AVAILABLE WITH SUPPLIER Ships from our Auckland warehouse within 3-4 weeks

Found a better price? Request a price match

Deep Learning Approaches to Cloud Security

$451⁹⁹

Book Hero Magic created this recommendation. While it's new and still learning, it may not be perfect - your feedback is welcome! IS THIS YOUR NEXT READ?

You might enjoy this book if you're intrigued by the intersection of artificial intelligence and cybersecurity, particularly in how deep learning techniques can be applied to enhance cloud security. This book offers insightful explanations that could appeal to those looking to stay ahead in the rapidly evolving field of cloud technology security.

Deep Learning Approaches to Cloud Security

Description

Deep Learning Approaches to Cloud Security covers one of the most critical subjects in our society today: cloud security. This book explores solutions derived from evolving deep learning approaches, which enable computers to learn from experience and understand the world through a hierarchy of concepts, with each concept defined in relation to simpler concepts.

Deep learning is the fastest-growing field in computer science. Its algorithms and techniques are instrumental in various domains, including automatic machine translation, handwriting generation, visual recognition, fraud detection, and detecting developmental delays in children. However, the successful application of deep learning techniques or algorithms in these areas requires integrative research among experts from diverse disciplines, ranging from data science to visualisation. This book provides state-of-the-art approaches to deep learning in these domains, focusing on areas like detection and prediction, future framework development, building service systems, and analytical aspects. Techniques such as artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms are employed throughout the book. This volume is crucial for modelling and performance prediction of efficient cloud security systems, adding a new dimension to this rapidly evolving field.

This groundbreaking new volume presents the latest topics and trends in deep learning, bridging the research gap and offering solutions to the challenges engineers or scientists face daily in this field. Whether you are a seasoned engineer or a student, this book is an essential addition to any library.

Deep Learning Approaches to Cloud Security:

Is the first volume of its kind to explore the latest trends and innovations in cloud security through deep learning approaches.
Covers significant innovations, such as AI, data mining, and other evolving computing technologies related to cloud security.
Serves as a valuable reference for both veteran computer scientists or engineers and newcomers or students in this field.
Discusses not only the practical applications of these technologies but also the broader concepts and theories behind why these deep learning tools are essential not just for cloud security, but for society as a whole.

Audience: Computer scientists, scientists and engineers working with information technology, design, network security, and manufacturing, researchers in computers, electronics, and electrical and network security, integrated domain, and data analytics, and students in these areas.

Book Details

INFORMATION

ISBN: 9781119760528

Publisher: John Wiley & Sons Inc

Format: Hardback

Date Published: 25 January 2022

Country: United States

Imprint: Wiley-Scrivener

Contributors:

Edited by Rashmi Agrawal
Edited by Pramod Singh Rathore
Edited by Vishal Dutt
Edited by Satya Murthy Sasubilli
Edited by Srinivasa Rao Swarna
Edited by Pramod Singh Rathore

Audience: Professional and scholarly

DIMENSIONS

Spine width: 10.0mm

Width: 10.0mm

Height: 10.0mm

Weight: 454g

Pages: 304

Collections

Computing & Technology Education & Reference Non-Fiction

About the Author

Pramod Singh Rathore, PhD, is an assistant professor in the computer science and engineering department at the Aryabhatta Engineering College and Research Centre, Ajmer, Rajasthan, India and is also visiting faculty at the Government University, MDS Ajmer. He has over eight years of teaching experience and more than 45 publications in peer-reviewed journals, books, and conferences. He has also co-authored and edited numerous books with a variety of global publishers, such as the imprint, Wiley-Scrivener.

Vishal Dutt, PhD, received his doctorate in computer science from the University of Madras, and he is an assistant professor in the computer science and engineering department at the Aryabhatta Engineering College in Ajmer, as well as visiting faculty at Maharshi Dayanand Saraswati University in Ajmer. He has four years of teaching experience and has more than 22 publications in peer-reviewed scientific and technical journals. He has also been working as a freelance writer for more than six years in the fields of data analytics, Java, Assembly Programmer, Desktop Designer, and Android Developer.

Rashmi Agrawal, PhD, is a professor in the Department of Computer Applications at Manav Rachna International Institute of Research and Studies in Faridabad, India. She has over 18 years of experience in teaching and research and is a book series editor for a series on big data and machine learning. She has authored or coauthored numerous research papers in peer-reviewed scientific and technical journals and conferences and has also edited or authored books with a number of large book publishers, in imprints such as Wiley-Scrivener. She is also an active reviewer and editorial board member in various journals.

Satya Murthy Sasubilli is a solutions architect with the Huntington National Bank, having received his masters in computer applications from the University of Madras, India. He has more than 15 years of experience in cloud-based technologies like big data solutions, cloud infrastructure, digital analytics delivery, data warehousing, and many others. He has worked with many Fortune 500 organizations, such as Infosys, Capgemini, and others and is an active reviewer for several scientific and technical journals.

Srinivasa Rao Swarna is a program manager and senior data architect at Tata Consultancy Services in the USA. He received his BTech in chemical engineering from Jawaharlal Nehru Technological University, Hyderabad, India and completed his internship at Volkswagen AG, Wolfsburg, Germany in 2004. He has over 16 years of experience in this area, having worked with many Fortune 500 companies, and he is a frequent reviewer for several scientific and technical journals.