Convergence of Deep Learning in Cyber-IoT Systems and Security

This book analyzes the convergence of Deep Learning and Cyber-IoT systems and provides innovative solutions and implementation of deep learning-based models in cyber-IoT systems, while also addressing security issues. It is aimed at researchers and industry engineers in computer science, information technology, electronics and communication, cybersecurity, and cryptography.

Format: Hardback
Length: 480 pages
Publication date: 09 December 2022
Publisher: John Wiley & Sons Inc

In-depth exploration of Deep Learning-based cyber-IoT systems and security, poised to dominate the industry for the next decade.

The primary objective of this book is to highlight unconventional cryptographic approaches to enhance cyber security, encompassing both cyber-physical system security and IoT security through the utilization of deep learning techniques and analytics.

This comprehensive resource offers innovative solutions and practical implementations of deep learning-based models in cyber-IoT systems, while also shedding light on the inherent security vulnerabilities present in these systems. The book is structured into four parts.

Part I delves into the evolution of machine learning to deep learning, providing a foundational understanding of the topic.

Part II showcases a multitude of innovative solutions, algorithms, models, and implementations rooted in deep learning.

Part III delves into the realm of security and safety, exploring the implications of deep learning in these domains.

Part IV focuses on cyber-physical systems, discussing their unique characteristics and the security challenges they present, along with potential solutions.

This book is a valuable resource for researchers and industry engineers in computer science, information technology, electronics and communication, cybersecurity, and cryptography. It offers insightful perspectives and practical insights into the rapidly evolving field of deep learning and its application in cyber-IoT systems and security.

Weight: 742g
Dimension: 229 x 152 x 27 (mm)
ISBN-13: 9781119857211