Convergence of Deep Learning in Cyber-Iot Systems and Security

Rajdeep Chakraborty

ISBN 10: 111985721X / ISBN 13: 9781119857211

Editore: Wiley Dez 2022, 2022

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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.

Codice articolo 9781119857211

Dati bibliografici

• Titolo: Convergence of Deep Learning in Cyber-Iot Systems and Security
• Editore: Wiley Dez 2022
• Data di pubblicazione: 2022
• Lingua: Inglese
• ISBN 10: 111985721X
• ISBN 13: 9781119857211
• Rilegatura: Buch
• Condizione: Neu
• Dimensioni: 231 L x 152 A x 30 P (millimetri) 231 millimetri di larghezza per 152 millimetri di altezza per 30 millimetri di profondità
• Peso: 816 grammi

Descrizione articolo

Riassunto

CONVERGENCE OF DEEP LEARNING IN CYBER-IOT SYSTEMS AND SECURITY

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.

Informazioni sull?autore

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.