Convergence of Deep Learning in Cyber-IoT Systems and Security
Title | Convergence of Deep Learning in Cyber-IoT Systems and Security PDF eBook |
Author | Rajdeep Chakraborty |
Publisher | John Wiley & Sons |
Pages | 485 |
Release | 2022-12-08 |
Genre | Computers |
ISBN | 111985721X |
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.
Convergence of Deep Learning in Cyber-IoT Systems and Security
Title | Convergence of Deep Learning in Cyber-IoT Systems and Security PDF eBook |
Author | Rajdeep Chakraborty |
Publisher | John Wiley & Sons |
Pages | 485 |
Release | 2022-11-08 |
Genre | Computers |
ISBN | 111985766X |
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.
Machine Learning Approaches for Convergence of IoT and Blockchain
Title | Machine Learning Approaches for Convergence of IoT and Blockchain PDF eBook |
Author | Krishna Kant Singh |
Publisher | John Wiley & Sons |
Pages | 258 |
Release | 2021-08-10 |
Genre | Computers |
ISBN | 1119761743 |
MACHINE LEARNING APPROACHES FOR CONVERGENCE OF IOT AND BLOCKCHAIN The unique aspect of this book is that its focus is the convergence of machine learning, IoT, and blockchain in a single publication. Blockchain technology and the Internet of Things (IoT) are two of the most impactful trends to have emerged in the field of machine learning. Although there are a number of books available solely on the subjects of machine learning, IoT and blockchain technology, no such book has been available which focuses on machine learning techniques for IoT and blockchain convergence until now. Thus, this book is unique in terms of the topics it covers. Designed as an essential guide for all academicians, researchers, and those in industry who are working in related fields, this book will provide insights into the convergence of blockchain technology and the IoT with machine learning. Highlights of the book include: Examines many industries such as agriculture, manufacturing, food production, healthcare, the military, and IT Security of the Internet of Things using blockchain and AI Developing smart cities and transportation systems using machine learning and IoT Audience The target audience of this book is professionals and researchers (artificial intelligence specialists, systems engineers, information technologists) in the fields of machine learning, IoT, and blockchain technology.
Convergence of Deep Learning and Internet of Things: Computing and Technology
Title | Convergence of Deep Learning and Internet of Things: Computing and Technology PDF eBook |
Author | Kavitha, T. |
Publisher | IGI Global |
Pages | 371 |
Release | 2022-12-19 |
Genre | Computers |
ISBN | 166846277X |
Digital technology has enabled a number of internet-enabled devices that generate huge volumes of data from different systems. This large amount of heterogeneous data requires efficient data collection, processing, and analytical methods. Deep Learning is one of the latest efficient and feasible solutions that enable smart devices to function independently with a decision-making support system. Convergence of Deep Learning and Internet of Things: Computing and Technology contributes to technology and methodology perspectives in the incorporation of deep learning approaches in solving a wide range of issues in the IoT domain to identify, optimize, predict, forecast, and control emerging IoT systems. Covering topics such as data quality, edge computing, and attach detection and prediction, this premier reference source is a comprehensive resource for electricians, communications specialists, mechanical engineers, civil engineers, computer scientists, students and educators of higher education, librarians, researchers, and academicians.
Convergence of Blockchain, AI, and IoT
Title | Convergence of Blockchain, AI, and IoT PDF eBook |
Author | R. Indrakumari |
Publisher | CRC Press |
Pages | 207 |
Release | 2021-12-24 |
Genre | Computers |
ISBN | 1000519325 |
Convergence of Blockchain, AI, and IoT: Concepts and Challenges discusses the convergence of three powerful technologies that play into the digital revolution and blur the lines between biological, digital, and physical objects. This book covers novel algorithms, solutions for addressing issues in applications, security, authentication, and privacy. The book provides an overview of the clinical scientific research enabling smart diagnosis equipment through AI. It presents the role these technologies play in augmented reality and blockchain, covers digital currency managed with bitcoin, and discusses deep learning and how it can enhance human thoughts and behaviors. Targeted audiences range from those interested in the technical revolution of blockchain, big data and the Internet of Things, to research scholars and the professional market.
Deep Learning for Security and Privacy Preservation in IoT
Title | Deep Learning for Security and Privacy Preservation in IoT PDF eBook |
Author | Aaisha Makkar |
Publisher | Springer Nature |
Pages | 186 |
Release | 2022-04-03 |
Genre | Computers |
ISBN | 9811661863 |
This book addresses the issues with privacy and security in Internet of things (IoT) networks which are susceptible to cyber-attacks and proposes deep learning-based approaches using artificial neural networks models to achieve a safer and more secured IoT environment. Due to the inadequacy of existing solutions to cover the entire IoT network security spectrum, the book utilizes artificial neural network models, which are used to classify, recognize, and model complex data including images, voice, and text, to enhance the level of security and privacy of IoT. This is applied to several IoT applications which include wireless sensor networks (WSN), meter reading transmission in smart grid, vehicular ad hoc networks (VANET), industrial IoT and connected networks. The book serves as a reference for researchers, academics, and network engineers who want to develop enhanced security and privacy features in the design of IoT systems.
Deep Learning Techniques for IoT Security and Privacy
Title | Deep Learning Techniques for IoT Security and Privacy PDF eBook |
Author | Mohamed Abdel-Basset |
Publisher | Springer Nature |
Pages | 273 |
Release | 2021-12-05 |
Genre | Computers |
ISBN | 3030890252 |
This book states that the major aim audience are people who have some familiarity with Internet of things (IoT) but interested to get a comprehensive interpretation of the role of deep Learning in maintaining the security and privacy of IoT. A reader should be friendly with Python and the basics of machine learning and deep learning. Interpretation of statistics and probability theory will be a plus but is not certainly vital for identifying most of the book's material.