Deep Learning for Security and Privacy Preservation in IoT

This book proposes deep learning-based approaches using artificial neural network models to enhance the security and privacy of Internet of Things (IoT) networks, covering various applications such as WSN, smart grid, VANET, and industrial IoT.

Format: Paperback / softback
Length: 179 pages
Publication date: 05 April 2023
Publisher: Springer Verlag, Singapore

The Internet of Things (IoT) has emerged as a revolutionary technology that has the potential to transform various aspects of our lives, from smart homes to smart cities. However, with this growth comes a significant concern for privacy and security. IoT networks are vulnerable to cyber-attacks, which can lead to unauthorized access, data theft, and even physical harm. This book aims to address these issues and propose deep learning-based approaches using artificial neural network models to achieve a safer and more secured IoT environment.

Existing solutions to cover the entire IoT network security spectrum are inadequate, as they focus on specific aspects of security and fail to address the complex challenges posed by IoT. Artificial neural network models, on the other hand, have the ability to classify, recognize, and model complex data, including images, voice, and text. This enables them to enhance the level of security and privacy of IoT.

The book applies these artificial neural network models to several IoT applications, such as wireless sensor networks (WSN), meter reading transmission in smart grid, vehicular ad hoc networks (VANET), industrial IoT, and connected networks. By leveraging the power of deep learning, the book aims to develop enhanced security and privacy features in the design of IoT systems.

The book is written for researchers, academics, and network engineers who want to develop enhanced security and privacy features in the design of IoT systems. It provides a comprehensive overview of the current state of IoT security, the challenges faced by IoT, and the potential solutions using deep learning-based approaches. The book also includes case studies and practical examples to illustrate the effectiveness of the proposed approaches.

In conclusion, this book is a valuable resource for anyone interested in developing secure and privacy-friendly IoT systems. It provides a comprehensive understanding of the current state of IoT security, the challenges faced by IoT, and the potential solutions using deep learning-based approaches. By leveraging the power of artificial neural network models, we can create a safer and more secure IoT environment that benefits everyone.

Weight: 302g
Dimension: 235 x 155 (mm)
ISBN-13: 9789811661884
Edition number: 1st ed. 2021