Convergence of Deep Learning in Cyber-Iot Systems and Security
Language: English
Published by Wiley Dez 2022, 2022
Series: Book 12 of 16 - Artificial Intelligence and Soft Computing for Industrial Transformation
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
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Add to basketItem description from seller
Neuware - CONVERGENCE OF DEEP LEARNING IN CYBER-IOT SYSTEMS AND SECURITYIn-depth analysis of Deep Learning-based cyber-IoT systems and security which will be the industry leader for the next ten years.The main goal of this book is to bring to the fore unconventional cryptographic methods to provide cyber security, including cyber-physical system security and IoT security through deep learning techniques and analytics with the study of all these systems.This book provides innovative solutions and implementation of deep learning-based models in cyber-IoT systems, as well as the exposed security issues in these systems. The 20 chapters are organized into four parts. Part I gives the various approaches that have evolved from machine learning to deep learning. Part II presents many innovative solutions, algorithms, models, and implementations based on deep learning. Part III covers security and safety aspects with deep learning. Part IV details cyber-physical systems as well as a discussion on the security and threats in cyber-physical systems with probable solutions.AudienceResearchers and industry engineers in computer science, information technology, electronics and communication, cybersecurity and cryptography.…
Seller Inventory # 9781119857211
- Title
- Convergence of Deep Learning in Cyber-Iot Systems and Security
- Author
- Rajdeep Chakraborty
- Publisher
- Wiley Dez 2022
- Publication year
- 2022
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 111985721X
- ISBN 13
- 9781119857211
- Item weight
- 816 grams
- Dimensions
- 231x152x30 mm
- Series
- Book 12 of 16: Artificial Intelligence and Soft Computing for Industrial Transformation
In-depth analysis of Deep Learning-based cyber-IoT systems and security which will be the industry leader for the next ten years.
The main goal of this book is to bring to the fore unconventional cryptographic methods to provide cyber security, including cyber-physical system security and IoT security through deep learning techniques and analytics with the study of all these systems.
This book provides innovative solutions and implementation of deep learning-based models in cyber-IoT systems, as well as the exposed security issues in these systems. The 20 chapters are organized into four parts. Part I gives the various approaches that have evolved from machine learning to deep learning. Part II presents many innovative solutions, algorithms, models, and implementations based on deep learning. Part III covers security and safety aspects with deep learning. Part IV details cyber-physical systems as well as a discussion on the security and threats in cyber-physical systems with probable solutions.
Audience
Researchers and industry engineers in computer science, information technology, electronics and communication, cybersecurity and cryptography.
"Synopsis" may belong to another edition of this title.
About the Author
Rajdeep Chakraborty, PhD, is an assistant professor in the Department of Computer Science and Engineering, Netaji Subhash Engineering College, Kolkata, India. His fields of interest are mainly in cryptography and computer security. He was awarded the Adarsh Vidya Saraswati Rashtriya Puraskar, National Award of Excellence 2019 conferred by Glacier Journal Research Foundation,
Anupam Ghosh, PhD, is a professor in the Department of Computer Science and Engineering, Netaji Subhash Engineering College, Kolkata, India. He has published more than 80 international papers in reputed international journals and conferences. His fields of interest are mainly in AI, machine learning, deep learning, image processing, soft computing, bioinformatics, IoT, and data mining.
Jyotsna Kumar Mandal, PhD, has more than 30 years of industry and academic experience. His fields of interest are coding theory, data and network security, remote sensing & GIS-based applications, data compression error corrections, information security, watermarking, steganography and document authentication, image processing, visual cryptography, MANET, wireless and mobile computing/security, unify computing, chaos theory, and applications.
S. Balamurugan, PhD, is the Director of Research and Development, Intelligent Research Consultancy Services (iRCS), Coimbatore, Tamilnadu, India. He is also Director of the Albert Einstein Engineering and Research Labs (AEER Labs), as well as Vice-Chairman, Renewable Energy Society of India (RESI), India. He has published 45 books, 200+ international journals/ conferences, and 35 patents.
"About the title" may belong to another edition of this title.
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