Deep Learning Techniques For Iot Security And Privacy
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Deep Learning Techniques For Iot Security And Privacy
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Author : Mohamed Abdel-Basset
language : en
Publisher: Springer Nature
Release Date : 2021-12-05
Deep Learning Techniques For Iot Security And Privacy written by Mohamed Abdel-Basset and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-05 with Computers categories.
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.
Deep Learning Approaches For Security Threats In Iot Environments
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Author : Mohamed Abdel-Basset
language : en
Publisher: John Wiley & Sons
Release Date : 2022-12-08
Deep Learning Approaches For Security Threats In Iot Environments written by Mohamed Abdel-Basset and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-08 with Computers categories.
Deep Learning Approaches for Security Threats in IoT Environments An expert discussion of the application of deep learning methods in the IoT security environment In Deep Learning Approaches for Security Threats in IoT Environments, a team of distinguished cybersecurity educators deliver an insightful and robust exploration of how to approach and measure the security of Internet-of-Things (IoT) systems and networks. In this book, readers will examine critical concepts in artificial intelligence (AI) and IoT, and apply effective strategies to help secure and protect IoT networks. The authors discuss supervised, semi-supervised, and unsupervised deep learning techniques, as well as reinforcement and federated learning methods for privacy preservation. This book applies deep learning approaches to IoT networks and solves the security problems that professionals frequently encounter when working in the field of IoT, as well as providing ways in which smart devices can solve cybersecurity issues. Readers will also get access to a companion website with PowerPoint presentations, links to supporting videos, and additional resources. They’ll also find: A thorough introduction to artificial intelligence and the Internet of Things, including key concepts like deep learning, security, and privacy Comprehensive discussions of the architectures, protocols, and standards that form the foundation of deep learning for securing modern IoT systems and networks In-depth examinations of the architectural design of cloud, fog, and edge computing networks Fulsome presentations of the security requirements, threats, and countermeasures relevant to IoT networks Perfect for professionals working in the AI, cybersecurity, and IoT industries, Deep Learning Approaches for Security Threats in IoT Environments will also earn a place in the libraries of undergraduate and graduate students studying deep learning, cybersecurity, privacy preservation, and the security of IoT networks.
Iot
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Author : Souvik Pal
language : en
Publisher: CRC Press
Release Date : 2020-06-03
Iot written by Souvik Pal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-03 with Technology & Engineering categories.
IOT: Security and Privacy Paradigm covers the evolution of security and privacy issues in the Internet of Things (IoT). It focuses on bringing all security and privacy related technologies into one source, so that students, researchers, and practitioners can refer to this book for easy understanding of IoT security and privacy issues. This edited book uses Security Engineering and Privacy-by-Design principles to design a secure IoT ecosystem and to implement cyber-security solutions. This book takes the readers on a journey that begins with understanding the security issues in IoT-enabled technologies and how it can be applied in various aspects. It walks readers through engaging with security challenges and builds a safe infrastructure for IoT devices. The book helps readers gain an understand of security architecture through IoT and describes the state of the art of IoT countermeasures. It also differentiates security threats in IoT-enabled infrastructure from traditional ad hoc or infrastructural networks, and provides a comprehensive discussion on the security challenges and solutions in RFID, WSNs, in IoT. This book aims to provide the concepts of related technologies and novel findings of the researchers through its chapter organization. The primary audience includes specialists, researchers, graduate students, designers, experts and engineers who are focused on research and security related issues. Souvik Pal, PhD, has worked as Assistant Professor in Nalanda Institute of Technology, Bhubaneswar, and JIS College of Engineering, Kolkata (NAAC "A" Accredited College). He is the organizing Chair and Plenary Speaker of RICE Conference in Vietnam; and organizing co-convener of ICICIT, Tunisia. He has served in many conferences as chair, keynote speaker, and he also chaired international conference sessions and presented session talks internationally. His research area includes Cloud Computing, Big Data, Wireless Sensor Network (WSN), Internet of Things, and Data Analytics. Vicente García-Díaz, PhD, is an Associate Professor in the Department of Computer Science at the University of Oviedo (Languages and Computer Systems area). He is also the editor of several special issues in prestigious journals such as Scientific Programming and International Journal of Interactive Multimedia and Artificial Intelligence. His research interests include eLearning, machine learning and the use of domain specific languages in different areas. Dac-Nhuong Le, PhD, is Deputy-Head of Faculty of Information Technology, and Vice-Director of Information Technology Apply and Foreign Language Training Center, Haiphong University, Vietnam. His area of research includes: evaluation computing and approximate algorithms, network communication, security and vulnerability, network performance analysis and simulation, cloud computing, IoT and image processing in biomedical. Presently, he is serving on the editorial board of several international journals and has authored nine computer science books published by Springer, Wiley, CRC Press, Lambert Publication, and Scholar Press.
Handbook Of Research On Machine And Deep Learning Applications For Cyber Security
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Author : Padmavathi Ganapathi
language : en
Publisher: IGI Global, Information Science Reference
Release Date : 2019-07-26
Handbook Of Research On Machine And Deep Learning Applications For Cyber Security written by Padmavathi Ganapathi and has been published by IGI Global, Information Science Reference this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-26 with Computers categories.
"This book explores the use of machine learning and deep learning applications in the areas of cyber security and cyber-attack handling mechanisms"--
Learning Techniques For The Internet Of Things
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Author : Praveen Kumar Donta
language : en
Publisher: Springer Nature
Release Date : 2024-02-19
Learning Techniques For The Internet Of Things written by Praveen Kumar Donta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-19 with Computers categories.
The book is structured into thirteen chapters; each comes with its own dedicated contributions and future research directions. Chapter 1 introduces IoT and the use of Edge computing, particularly cloud computing, and mobile edge computing. This chapter also mentions the use of edge computing in various real-time applications such as healthcare, manufacturing, agriculture, and transportation. Chapter 2 motivates mathematical modeling for federated learning systems with respect to IoT and its applications. Further Chapter 3 extends the discussion of federated learning for IoT, which has emerged as a privacy-preserving distributed machine learning approach. Chapter 4 provides various machine learning techniques in Industrial IoT to deliver rapid and accurate data analysis, essential for enhancing production quality, sustainability, and safety. Chapter discusses the potential role of data-driven technologies, such as Artificial Intelligence, Machine Learning, and Deep Learning, focuses on their integration with IoT communication technologies. Chapter 6 presents the requirements and challenges to realize IoT deployments in smart cities, including sensing infrastructure, Artificial Intelligence, computing platforms, and enabling communications technologies such as 5G networks. To highlight these challenges in practice, the chapter also presents a real-world case study of a city-scale deployment of IoT air quality monitoring within Helsinki city. Chapter 7 uses digital twins within smart cities to enhance economic progress and facilitate prompt decision-making regarding situational awareness. Chapter 8 provides insights into using Multi-Objective reinforcement learning in future IoT networks, especially for an efficient decision-making system. Chapter 9 offers a comprehensive review of intelligent inference approaches, with a specific emphasis on reducing inference time and minimizing transmitted bandwidth between IoT devices and the cloud. Chapter 10 summarizes the applications of deep learning models in various IoT fields. This chapter also presents an in-depth study of these techniques to examine new horizons of applications of deep learning models in different areas of IoT. Chapter 11 explores the integration of Quantum Key Distribution (QKD) into IoT systems. It delves into the potential benefits, challenges, and practical considerations of incorporating QKD into IoT networks. In chapter 12, a comprehensive overview regarding the current state of quantum IoT in the context of smart healthcare is presented, along with its applications, benefits, challenges, and prospects for the future. Chapter 13 proposes a blockchain-based architecture for securing and managing IoT data in intelligent transport systems, offering advantages like immutability, decentralization, and enhanced security.
Research Anthology On Privatizing And Securing Data
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Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2021-04-23
Research Anthology On Privatizing And Securing Data written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-23 with Computers categories.
With the immense amount of data that is now available online, security concerns have been an issue from the start, and have grown as new technologies are increasingly integrated in data collection, storage, and transmission. Online cyber threats, cyber terrorism, hacking, and other cybercrimes have begun to take advantage of this information that can be easily accessed if not properly handled. New privacy and security measures have been developed to address this cause for concern and have become an essential area of research within the past few years and into the foreseeable future. The ways in which data is secured and privatized should be discussed in terms of the technologies being used, the methods and models for security that have been developed, and the ways in which risks can be detected, analyzed, and mitigated. The Research Anthology on Privatizing and Securing Data reveals the latest tools and technologies for privatizing and securing data across different technologies and industries. It takes a deeper dive into both risk detection and mitigation, including an analysis of cybercrimes and cyber threats, along with a sharper focus on the technologies and methods being actively implemented and utilized to secure data online. Highlighted topics include information governance and privacy, cybersecurity, data protection, challenges in big data, security threats, and more. This book is essential for data analysts, cybersecurity professionals, data scientists, security analysts, IT specialists, practitioners, researchers, academicians, and students interested in the latest trends and technologies for privatizing and securing data.
Machine Learning Approaches For Convergence Of Iot And Blockchain
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Author : Krishna Kant Singh
language : en
Publisher: John Wiley & Sons
Release Date : 2021-08-10
Machine Learning Approaches For Convergence Of Iot And Blockchain written by Krishna Kant Singh and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-10 with Computers categories.
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.
Network Optimization In Intelligent Internet Of Things Applications
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Author : Payal Khurana Batra
language : en
Publisher: CRC Press
Release Date : 2024-09-25
Network Optimization In Intelligent Internet Of Things Applications written by Payal Khurana Batra and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-25 with Computers categories.
Network Optimization in Intelligent Internet of Things Applications: Principles and Challenges sheds light on the optimization methods that form the basis of effective communication between networked devices. It is an excellent resource as it provides readers with a thorough understanding of the methods, ideas, and tactics essential to attaining seamless connectivity and improving performance. This book presents the fundamental ideas that govern network optimization, from maximizing throughput and lowering latency to handling a variety of communication protocols and minimizing energy use. It also addresses scalability issues, security flaws, and constantly changing IoT environments along with optimization techniques. This book uses cutting-edge research and real-world examples to give readers the knowledge and skills to address the complex problems associated with network optimization in intelligent IoT applications. It also examines machine learning-driven predictive analytics, robust security protocols, flexible routing algorithms, and the integration of edge computing - all crucial instruments for overcoming obstacles and attaining peak performance. This book provides a comprehensive understanding of the principles, challenges, and cutting-edge solutions in IoT network optimization for all kinds of readers, whether it is students, academicians, researchers, or industry professionals. This book unleashes the potential of networked smart devices, which can be unleashed in various sectors.
Deep Learning In Internet Of Things For Next Generation Healthcare
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Author : Lavanya Sharma
language : en
Publisher: CRC Press
Release Date : 2024-06-18
Deep Learning In Internet Of Things For Next Generation Healthcare written by Lavanya Sharma and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-18 with Computers categories.
This book presents the latest developments in deep learning-enabled healthcare tools and technologies and offers practical ideas for using the IoT with deep learning (motion-based object data) to deal with human dynamics and challenges including critical application domains, technologies, medical imaging, drug discovery, insurance fraud detection and solutions to handle relevant challenges. This book covers real-time healthcare applications, novel solutions, current open challenges, and the future of deep learning for next-generation healthcare. It includes detailed analysis of the utilization of the IoT with deep learning and its underlying technologies in critical application areas of emergency departments such as drug discovery, medical imaging, fraud detection, Alzheimer's disease, and genomes. Presents practical approaches of using the IoT with deep learning vision and how it deals with human dynamics Offers novel solution for medical imaging including skin lesion detection, cancer detection, enhancement techniques for MRI images, automated disease prediction, fraud detection, genomes, and many more Includes the latest technological advances in the IoT and deep learning with their implementations in healthcare Combines deep learning and analysis in the unified framework to understand both IoT and deep learning applications Covers the challenging issues related to data collection by sensors, detection and tracking of moving objects and solutions to handle relevant challenges Postgraduate students and researchers in the departments of computer science, working in the areas of the IoT, deep learning, machine learning, image processing, big data, cloud computing, and remote sensing will find this book useful.
Proceedings Of The Third International Conference On Information Management And Machine Intelligence
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Author : Dinesh Goyal
language : en
Publisher: Springer Nature
Release Date : 2022-08-03
Proceedings Of The Third International Conference On Information Management And Machine Intelligence written by Dinesh Goyal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-03 with Technology & Engineering categories.
This book features selected papers presented at Third International Conference on International Conference on Information Management and Machine Intelligence (ICIMMI 2021) held at Poornima Institute of Engineering & Technology, Jaipur, Rajasthan, India during 23 – 24 December 2021. It covers a range of topics, including data analytics; AI; machine and deep learning; information management, security, processing techniques and interpretation; applications of artificial intelligence in soft computing and pattern recognition; cloud-based applications for machine learning; application of IoT in power distribution systems; as well as wireless sensor networks and adaptive wireless communication.