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This book covers IoT and Big Data from a technical and business point of view. The book explains the design principles, algorithms, technical knowledge, and marketing for IoT systems. It emphasizes applications of big data and IoT. It includes scientific algorithms and key techniques for fusion of both areas. Real case applications from different industries are offering to facilitate ease of understanding the approach. The book goes on to address the significance of security algorithms in combing IoT and big data which is currently evolving in communication technologies. The book is written for researchers, professionals, and academicians from interdisciplinary and transdisciplinary areas. The readers will get an opportunity to know the conceptual ideas with step-by-step pragmatic examples which makes ease of understanding no matter the level of the reader.
Book Synopsis Securing IoT and Big Data by : Vijayalakshmi Saravanan
Download or read book Securing IoT and Big Data written by Vijayalakshmi Saravanan and published by CRC Press. This book was released on 2020-12-17 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers IoT and Big Data from a technical and business point of view. The book explains the design principles, algorithms, technical knowledge, and marketing for IoT systems. It emphasizes applications of big data and IoT. It includes scientific algorithms and key techniques for fusion of both areas. Real case applications from different industries are offering to facilitate ease of understanding the approach. The book goes on to address the significance of security algorithms in combing IoT and big data which is currently evolving in communication technologies. The book is written for researchers, professionals, and academicians from interdisciplinary and transdisciplinary areas. The readers will get an opportunity to know the conceptual ideas with step-by-step pragmatic examples which makes ease of understanding no matter the level of the reader.
With the proliferation of devices connected to the internet and connected to each other, the volume of data collected, stored, and processed is increasing every day, which brings new challenges in terms of information security. As big data expands with the help of public clouds, traditional security solutions tailored to private computing infrastructures and confined to a well-defined security perimeter, such as firewalls and demilitarized zones (DMZs), are no longer effective. New security functions are required to work over the heterogenous composition of diverse hardware, operating systems, and network domains. Security, Privacy, and Forensics Issues in Big Data is an essential research book that examines recent advancements in big data and the impact that these advancements have on information security and privacy measures needed for these networks. Highlighting a range of topics including cryptography, data analytics, and threat detection, this is an excellent reference source for students, software developers and engineers, security analysts, IT consultants, academicians, researchers, and professionals.
Book Synopsis Security, Privacy, and Forensics Issues in Big Data by : Joshi, Ramesh C.
Download or read book Security, Privacy, and Forensics Issues in Big Data written by Joshi, Ramesh C. and published by IGI Global. This book was released on 2019-08-30 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the proliferation of devices connected to the internet and connected to each other, the volume of data collected, stored, and processed is increasing every day, which brings new challenges in terms of information security. As big data expands with the help of public clouds, traditional security solutions tailored to private computing infrastructures and confined to a well-defined security perimeter, such as firewalls and demilitarized zones (DMZs), are no longer effective. New security functions are required to work over the heterogenous composition of diverse hardware, operating systems, and network domains. Security, Privacy, and Forensics Issues in Big Data is an essential research book that examines recent advancements in big data and the impact that these advancements have on information security and privacy measures needed for these networks. Highlighting a range of topics including cryptography, data analytics, and threat detection, this is an excellent reference source for students, software developers and engineers, security analysts, IT consultants, academicians, researchers, and professionals.
This provides a comprehensive overview of the key principles of security concerns surrounding the upcoming Internet of Things (IoT), and introduces readers to the protocols adopted in the IoT. It also analyses the vulnerabilities, attacks and defense mechanisms, highlighting the security issues in the context of big data. Lastly, trust management approaches and ubiquitous learning applications are examined in detail. As such, the book sets the stage for developing and securing IoT applications both today and in the future.
Book Synopsis Ubiquitous Computing and Computing Security of IoT by : N. Jeyanthi
Download or read book Ubiquitous Computing and Computing Security of IoT written by N. Jeyanthi and published by Springer. This book was released on 2018-10-03 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt: This provides a comprehensive overview of the key principles of security concerns surrounding the upcoming Internet of Things (IoT), and introduces readers to the protocols adopted in the IoT. It also analyses the vulnerabilities, attacks and defense mechanisms, highlighting the security issues in the context of big data. Lastly, trust management approaches and ubiquitous learning applications are examined in detail. As such, the book sets the stage for developing and securing IoT applications both today and in the future.
The increase in connected devices in the internet of things (IoT) is leading to an exponential increase in the data that an organization is required to manage. To successfully utilize IoT in businesses, big data analytics are necessary in order to efficiently sort through the increased data. The combination of big data and IoT can thus enable new monitoring services and powerful processing of sensory data streams. The Handbook of Research on Big Data and the IoT is a pivotal reference source that provides vital research on emerging trends and recent innovative applications of big data and IoT, challenges facing organizations and the implications of these technologies on society, and best practices for their implementation. While highlighting topics such as bootstrapping, data fusion, and graph mining, this publication is ideally designed for IT specialists, managers, policymakers, analysts, software engineers, academicians, and researchers.
Book Synopsis Handbook of Research on Big Data and the IoT by : Kaur, Gurjit
Download or read book Handbook of Research on Big Data and the IoT written by Kaur, Gurjit and published by IGI Global. This book was released on 2019-03-29 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt: The increase in connected devices in the internet of things (IoT) is leading to an exponential increase in the data that an organization is required to manage. To successfully utilize IoT in businesses, big data analytics are necessary in order to efficiently sort through the increased data. The combination of big data and IoT can thus enable new monitoring services and powerful processing of sensory data streams. The Handbook of Research on Big Data and the IoT is a pivotal reference source that provides vital research on emerging trends and recent innovative applications of big data and IoT, challenges facing organizations and the implications of these technologies on society, and best practices for their implementation. While highlighting topics such as bootstrapping, data fusion, and graph mining, this publication is ideally designed for IT specialists, managers, policymakers, analysts, software engineers, academicians, and researchers.
This book discusses the evolution of security and privacy issues in the Internet of Things (IoT). The book focuses on assembling all security- and privacy-related technologies into a single source so that students, researchers, academics, and those in the industry can easily understand the IoT security and privacy issues. This edited book discusses the use of 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 security issues in IoT-enabled technologies and how these can be applied in various sectors. It walks readers through engaging with security challenges and building a safe infrastructure for IoT devices. The book helps researchers and practitioners understand the security architecture of IoT and the state-of-the-art in 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 and WSNs in IoT. This book aims to highlight the concepts of related technologies and novel findings by researchers through its chapter organization. The primary audience comprises specialists, researchers, graduate students, designers, experts, and engineers undertaking research on security-related issues.
Book Synopsis Privacy Vulnerabilities and Data Security Challenges in the IoT by : Shivani Agarwal
Download or read book Privacy Vulnerabilities and Data Security Challenges in the IoT written by Shivani Agarwal and published by CRC Press. This book was released on 2020-11-23 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the evolution of security and privacy issues in the Internet of Things (IoT). The book focuses on assembling all security- and privacy-related technologies into a single source so that students, researchers, academics, and those in the industry can easily understand the IoT security and privacy issues. This edited book discusses the use of 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 security issues in IoT-enabled technologies and how these can be applied in various sectors. It walks readers through engaging with security challenges and building a safe infrastructure for IoT devices. The book helps researchers and practitioners understand the security architecture of IoT and the state-of-the-art in 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 and WSNs in IoT. This book aims to highlight the concepts of related technologies and novel findings by researchers through its chapter organization. The primary audience comprises specialists, researchers, graduate students, designers, experts, and engineers undertaking research on security-related issues.
BIG DATA ANALYTICS FOR INTERNET OF THINGS Discover the latest developments in IoT Big Data with a new resource from established and emerging leaders in the field Big Data Analytics for Internet of Things delivers a comprehensive overview of all aspects of big data analytics in Internet of Things (IoT) systems. The book includes discussions of the enabling technologies of IoT data analytics, types of IoT data analytics, challenges in IoT data analytics, demand for IoT data analytics, computing platforms, analytical tools, privacy, and security. The distinguished editors have included resources that address key techniques in the analysis of IoT data. The book demonstrates how to select the appropriate techniques to unearth valuable insights from IoT data and offers novel designs for IoT systems. With an abiding focus on practical strategies with concrete applications for data analysts and IoT professionals, Big Data Analytics for Internet of Things also offers readers: A thorough introduction to the Internet of Things, including IoT architectures, enabling technologies, and applications An exploration of the intersection between the Internet of Things and Big Data, including IoT as a source of Big Data, the unique characteristics of IoT data, etc. A discussion of the IoT data analytics, including the data analytical requirements of IoT data and the types of IoT analytics, including predictive, descriptive, and prescriptive analytics A treatment of machine learning techniques for IoT data analytics Perfect for professionals, industry practitioners, and researchers engaged in big data analytics related to IoT systems, Big Data Analytics for Internet of Things will also earn a place in the libraries of IoT designers and manufacturers interested in facilitating the efficient implementation of data analytics strategies.
Book Synopsis Big Data Analytics for Internet of Things by : Tausifa Jan Saleem
Download or read book Big Data Analytics for Internet of Things written by Tausifa Jan Saleem and published by John Wiley & Sons. This book was released on 2021-04-20 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: BIG DATA ANALYTICS FOR INTERNET OF THINGS Discover the latest developments in IoT Big Data with a new resource from established and emerging leaders in the field Big Data Analytics for Internet of Things delivers a comprehensive overview of all aspects of big data analytics in Internet of Things (IoT) systems. The book includes discussions of the enabling technologies of IoT data analytics, types of IoT data analytics, challenges in IoT data analytics, demand for IoT data analytics, computing platforms, analytical tools, privacy, and security. The distinguished editors have included resources that address key techniques in the analysis of IoT data. The book demonstrates how to select the appropriate techniques to unearth valuable insights from IoT data and offers novel designs for IoT systems. With an abiding focus on practical strategies with concrete applications for data analysts and IoT professionals, Big Data Analytics for Internet of Things also offers readers: A thorough introduction to the Internet of Things, including IoT architectures, enabling technologies, and applications An exploration of the intersection between the Internet of Things and Big Data, including IoT as a source of Big Data, the unique characteristics of IoT data, etc. A discussion of the IoT data analytics, including the data analytical requirements of IoT data and the types of IoT analytics, including predictive, descriptive, and prescriptive analytics A treatment of machine learning techniques for IoT data analytics Perfect for professionals, industry practitioners, and researchers engaged in big data analytics related to IoT systems, Big Data Analytics for Internet of Things will also earn a place in the libraries of IoT designers and manufacturers interested in facilitating the efficient implementation of data analytics strategies.
The integration of fog computing with the resource-limited Internet of Things (IoT) network formulates the concept of the fog-enabled IoT system. Due to a large number of IoT devices, the IoT is a main source of Big Data. A large volume of sensing data is generated by IoT systems such as smart cities and smart-grid applications. A fundamental research issue is how to provide a fast and efficient data analytics solution for fog-enabled IoT systems. Big Data Analytics in Fog-Enabled IoT Networks: Towards a Privacy and Security Perspective focuses on Big Data analytics in a fog-enabled-IoT system and provides a comprehensive collection of chapters that touch on different issues related to healthcare systems, cyber-threat detection, malware detection, and the security and privacy of IoT Big Data and IoT networks. This book also emphasizes and facilitates a greater understanding of various security and privacy approaches using advanced artificial intelligence and Big Data technologies such as machine and deep learning, federated learning, blockchain, and edge computing, as well as the countermeasures to overcome the vulnerabilities of the fog-enabled IoT system.
Book Synopsis Big Data Analytics in Fog-Enabled IoT Networks by : Govind P. Gupta
Download or read book Big Data Analytics in Fog-Enabled IoT Networks written by Govind P. Gupta and published by CRC Press. This book was released on 2023-04-19 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: The integration of fog computing with the resource-limited Internet of Things (IoT) network formulates the concept of the fog-enabled IoT system. Due to a large number of IoT devices, the IoT is a main source of Big Data. A large volume of sensing data is generated by IoT systems such as smart cities and smart-grid applications. A fundamental research issue is how to provide a fast and efficient data analytics solution for fog-enabled IoT systems. Big Data Analytics in Fog-Enabled IoT Networks: Towards a Privacy and Security Perspective focuses on Big Data analytics in a fog-enabled-IoT system and provides a comprehensive collection of chapters that touch on different issues related to healthcare systems, cyber-threat detection, malware detection, and the security and privacy of IoT Big Data and IoT networks. This book also emphasizes and facilitates a greater understanding of various security and privacy approaches using advanced artificial intelligence and Big Data technologies such as machine and deep learning, federated learning, blockchain, and edge computing, as well as the countermeasures to overcome the vulnerabilities of the fog-enabled IoT system.
The Industry 4.0 revolution is changing the world around us. Artificial intelligence and machine learning, automation and robotics, big data, Internet of Things, augmented reality, virtual reality, and creativity are the tools of Industry 4.0. Improved collaboration is seen between smart systems and humans, which merges humans' critical and cognitive thinking abilities with highly accurate and fast industrial automation. Securing IoT in Industry 4.0 Applications with Blockchain examines the role of IoT in Industry 4.0 and how it can be made secure through various technologies including blockchain. The book begins with an in-depth look at IoT and discusses applications, architecture, technologies, tools, and programming languages. It then examines blockchain and cybersecurity, as well as how blockchain achieves cybersecurity. It also looks at cybercrimes and their preventive measures and issues related to IoT security and trust. Features An overview of how IoT is used to improve the performance of Industry 4.0 systems The evolution of the Industrial Internet of Things (IIoT), its proliferation and market share, and some examples across major industries An exploration of how smart farming is helping farmers prevent plant disease The concepts behind the Internet of Nano Things (IoNT), including the nanomachine and nanonetwork architecture and nano-communication paradigms A look at how blockchains can enhance cybersecurity in a variety of applications, including smart contracts, transferring financial instruments, and Public Key Infrastructure An overview of the structure and working of a blockchain, including the types, evolution, benefits, and applications of blockchain to industries A framework of technologies designed to shield networks, computers, and data from malware, vulnerabilities, and unauthorized activities An explanation of the automation system employed in industries along with its classification, functionality, flexibility, limitations, and applications
Book Synopsis Securing IoT in Industry 4.0 Applications with Blockchain by : P Kaliraj
Download or read book Securing IoT in Industry 4.0 Applications with Blockchain written by P Kaliraj and published by CRC Press. This book was released on 2021-12-03 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Industry 4.0 revolution is changing the world around us. Artificial intelligence and machine learning, automation and robotics, big data, Internet of Things, augmented reality, virtual reality, and creativity are the tools of Industry 4.0. Improved collaboration is seen between smart systems and humans, which merges humans' critical and cognitive thinking abilities with highly accurate and fast industrial automation. Securing IoT in Industry 4.0 Applications with Blockchain examines the role of IoT in Industry 4.0 and how it can be made secure through various technologies including blockchain. The book begins with an in-depth look at IoT and discusses applications, architecture, technologies, tools, and programming languages. It then examines blockchain and cybersecurity, as well as how blockchain achieves cybersecurity. It also looks at cybercrimes and their preventive measures and issues related to IoT security and trust. Features An overview of how IoT is used to improve the performance of Industry 4.0 systems The evolution of the Industrial Internet of Things (IIoT), its proliferation and market share, and some examples across major industries An exploration of how smart farming is helping farmers prevent plant disease The concepts behind the Internet of Nano Things (IoNT), including the nanomachine and nanonetwork architecture and nano-communication paradigms A look at how blockchains can enhance cybersecurity in a variety of applications, including smart contracts, transferring financial instruments, and Public Key Infrastructure An overview of the structure and working of a blockchain, including the types, evolution, benefits, and applications of blockchain to industries A framework of technologies designed to shield networks, computers, and data from malware, vulnerabilities, and unauthorized activities An explanation of the automation system employed in industries along with its classification, functionality, flexibility, limitations, and applications
This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020. Due to the COVID-19 outbreak problem, SPIoT-2020 conference was held online by Tencent Meeting. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.
Book Synopsis The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy by : John MacIntyre
Download or read book The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy written by John MacIntyre and published by Springer Nature. This book was released on 2020-11-03 with total page 907 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020. Due to the COVID-19 outbreak problem, SPIoT-2020 conference was held online by Tencent Meeting. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.
Security in IoT Social Networks takes a deep dive into security threats and risks, focusing on real-world social and financial effects. Mining and analyzing enormously vast networks is a vital part of exploiting Big Data. This book provides insight into the technological aspects of modeling, searching, and mining for corresponding research issues, as well as designing and analyzing models for resolving such challenges. The book will help start-ups grow, providing research directions concerning security mechanisms and protocols for social information networks. The book covers structural analysis of large social information networks, elucidating models and algorithms and their fundamental properties. Moreover, this book includes smart solutions based on artificial intelligence, machine learning, and deep learning for enhancing the performance of social information network security protocols and models. This book is a detailed reference for academicians, professionals, and young researchers. The wide range of topics provides extensive information and data for future research challenges in present-day social information networks. Provides several characteristics of social, network, and physical security associated with social information networks Presents the security mechanisms and events related to social information networks Covers emerging topics, such as network information structures like on-line social networks, heterogeneous and homogeneous information networks, and modern information networks Includes smart solutions based on artificial intelligence, machine learning, and deep learning for enhancing the performance of social information network security protocols and models
Book Synopsis Security in IoT Social Networks by : Fadi Al-Turjman
Download or read book Security in IoT Social Networks written by Fadi Al-Turjman and published by Academic Press. This book was released on 2020-11-03 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Security in IoT Social Networks takes a deep dive into security threats and risks, focusing on real-world social and financial effects. Mining and analyzing enormously vast networks is a vital part of exploiting Big Data. This book provides insight into the technological aspects of modeling, searching, and mining for corresponding research issues, as well as designing and analyzing models for resolving such challenges. The book will help start-ups grow, providing research directions concerning security mechanisms and protocols for social information networks. The book covers structural analysis of large social information networks, elucidating models and algorithms and their fundamental properties. Moreover, this book includes smart solutions based on artificial intelligence, machine learning, and deep learning for enhancing the performance of social information network security protocols and models. This book is a detailed reference for academicians, professionals, and young researchers. The wide range of topics provides extensive information and data for future research challenges in present-day social information networks. Provides several characteristics of social, network, and physical security associated with social information networks Presents the security mechanisms and events related to social information networks Covers emerging topics, such as network information structures like on-line social networks, heterogeneous and homogeneous information networks, and modern information networks Includes smart solutions based on artificial intelligence, machine learning, and deep learning for enhancing the performance of social information network security protocols and models
