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In today's data-driven society, the demand for secure, efficient, and decentralized data storage and communication solutions has become increasingly critical. This thesis explores the design and implementation of an end-to-end decentralized data model that leverages IOTA Streams and Swarm Storage technologies. The research begins by examining the limitations and challenges associated with centralized data models, such as single points of failure, data breaches, and high maintenance costs. To overcome these challenges, a decentralized approach is proposed, which combines the strengths of IOTA Streams and Swarm Storage. IOTA Streams is a messaging and data transmission protocol that provides a secure and tamper-proof communication layer. It allows for end-to-end encryption, data integrity verification, and fine-grained access control. By utilizing IOTA Streams, the proposed data model ensures the confidentiality and integrity of data throughout its lifecycle. Swarm Storage, on the other hand, offers a decentralized and fault-tolerant storage infrastructure. It employs a distributed hash table (DHT) network to store and retrieve data, enabling data redundancy, availability, and scalability. The integration of Swarm Storage within the data model enhances data persistence and accessibility in a decentralized manner. The thesis presents the design and implementation details of the end-to-end decentralized data model. It covers aspects such as data ingestion, transmission, storage, retrieval, and access control. The model incorporates cryptographic techniques, consensus mechanisms, and decentralized identifiers (DIDs) to establish a robust and secure data ecosystem. To evaluate the performance and effectiveness of the proposed data model, a series of experiments and simulations are conducted. The experiments assess factors such as data transfer speed, storage efficiency, fault tolerance, and resilience against attacks.The results validate the feasibility and advantages of the end-to-end decentralized data model based on IOTA Streams and Swarm Storage. In conclusion, this thesis demonstrates the potential of combining IOTA Streams and Swarm Storage to achieve an end-to-end decentralized data model. The proposed solution addresses the limitations of centralized data models and provides a secure, efficient, and scalable alternative for storing and transmitting data in decentralized environments. The findings of this research contribute to the field of decentralized systems and can guide the development of future decentralized data solutions.
This book presents practical as well as conceptual insights into the latest trends, tools, techniques and methodologies of blockchains for the Internet of Things. The decentralised Internet of Things (IoT) not only reduces infrastructure costs, but also provides a standardised peer-to-peer communication model for billions of transactions. However, there are significant security challenges associated with peer-to-peer communication. The decentralised concept of blockchain technology ensures transparent interactions between different parties, which are more secure and reliable thanks to distributed ledger and proof-of-work consensus algorithms. Blockchains allow trustless, peer-to-peer communication and have already proven their worth in the world of financial services. The blockchain can be implanted in IoT systems to deal with the issues of scale, trustworthiness and decentralisation, allowing billions of devices to share the same network without the need for additional resources. This book discusses the latest tools and methodology and concepts in the decentralised Internet of Things. Each chapter presents an in-depth investigation of the potential of blockchains in the Internet of Things, addressing the state-of-the-art in and future perspectives of the decentralised Internet of Things. Further, industry experts, researchers and academicians share their ideas and experiences relating to frontier technologies, breakthrough and innovative solutions and applications.
The Internet of Things (IoT) connects and shares data collected from smart devices in several domains, such as smart home, smart grid, and healthcare. According to Cisco, the number of connected devices is expected to reach 500 Billion by 2030. Five hundred zettabytes of data will be produced by tremendous machines and devices. Usually, these collected data are very sensitive and include metadata, such as location, time, and context. Their analysis allows the collector to deduce personal habits, behaviors and preferences of individuals. Besides, these collected data require the collaboration of several parties to be analyzed. Thus, due to the high level of IoT data sensitivity and lack of trust on the involved parties in the IoT environment, the collected data by different IoT devices should not be shared with each other, without enforcing data owner privacy. In fact, IoT data privacy has become a severe challenge nowadays, especially with the increasing legislation pressure. Our research focused on three complementary issues, mainly (i) the definition of a semantic layer designing the privacy requirements in the IoT domain, (ii) the IoT device monitoring and the enforcement of a privacy policy that matches both the data owner's privacy preferences and the data consumer's terms of service, and (iii) the establishment of an end-to-end privacy-preserving solution for IoT data in a decentralized architecture while eliminating the need to trust any involved IoT parties. To address these issues, our work contributes to three axes. First, we proposed a new European Legal compliant ontology for supporting preserving IoT PrivacY, called LIoPY that describes the IoT environment and the privacy requirements defined by privacy legislation and standards. Then, we defined a reasoning process whose goal is generating a privacy policy by matching between the data owner's privacy preferences and the data consumer's terms of service. This privacy policy specifies how the data will be handled once shared with a specific data consumer. In order to ensure this privacy policy enforcement, we introduced an IoT data privacy-preserving framework, called PrivBlockchain, in the second research axis. PrivBlockchain is an end-to-end privacy-preserving framework that involves several parties in the IoT environment for preserving IoT data privacy during the phases of collection, transmission, storage, and processing. The proposed framework relied on, on the one hand, the blockchain technology, thus supporting a decentralized architecture while eliminating the need to trust any involved IoT parties and, on the other hand, the smart contracts, thus supporting a machine-readable and self-enforcing privacy policy whose goal is to preserve the privacy during the whole data lifecycle, covering the collection, transmission, storage and processing phases. Finally, in the third axis, we designed and implemented the proposal in order to prove its feasibility and analyze its performances.
This book presents how federated learning helps to understand and learn from user activity in Internet of Things (IoT) applications while protecting user privacy. The authors first show how federated learning provides a unique way to build personalized models using data without intruding on users’ privacy. The authors then provide a comprehensive survey of state-of-the-art research on federated learning, giving the reader a general overview of the field. The book also investigates how a personalized federated learning framework is needed in cloud-edge architecture as well as in wireless-edge architecture for intelligent IoT applications. To cope with the heterogeneity issues in IoT environments, the book investigates emerging personalized federated learning methods that are able to mitigate the negative effects caused by heterogeneities in different aspects. The book provides case studies of IoT based human activity recognition to demonstrate the effectiveness of personalized federated learning for intelligent IoT applications, as well as multiple controller design and system analysis tools including model predictive control, linear matrix inequalities, optimal control, etc. This unique and complete co-design framework will benefit researchers, graduate students and engineers in the fields of control theory and engineering.
Provides comprehensive coverage of the current state of IoT, focusing on data processing infrastructure and techniques Written by experts in the field, this book addresses the IoT technology stack, from connectivity through data platforms to end-user case studies, and considers the tradeoffs between business needs and data security and privacy throughout. There is a particular emphasis on data processing technologies that enable the extraction of actionable insights from data to inform improved decision making. These include artificial intelligence techniques such as stream processing, deep learning and knowledge graphs, as well as data interoperability and the key aspects of privacy, security and trust. Additional aspects covered include: creating and supporting IoT ecosystems; edge computing; data mining of sensor datasets; and crowd-sourcing, amongst others. The book also presents several sections featuring use cases across a range of application areas such as smart energy, transportation, smart factories, and more. The book concludes with a chapter on key considerations when deploying IoT technologies in the enterprise, followed by a brief review of future research directions and challenges. The Internet of Things: From Data to Insight Provides a comprehensive overview of the Internet of Things technology stack with focus on data driven aspects from data modelling and processing to presentation for decision making Explains how IoT technology is applied in practice and the benefits being delivered. Acquaints readers that are new to the area with concepts, components, technologies, and verticals related to and enabled by IoT Gives IoT specialists a deeper insight into data and decision-making aspects as well as novel technologies and application areas Analyzes and presents important emerging technologies for the IoT arena Shows how different objects and devices can be connected to decision making processes at various levels of abstraction The Internet of Things: From Data to Insight will appeal to a wide audience, including IT and network specialists seeking a broad and complete understanding of IoT, CIOs and CIO teams, researchers in IoT and related fields, final year undergraduates, graduate students, post-graduates, and IT and science media professionals.
Smart communications are the concept in which smart appliances and devices are integrated into an application that runs in a smart hand-held device. The residents of a smart home can have complete control over their home’s electronic gadgets using wireless communications. These technologies can help people control gadgets in the home/office remotely and often simultaneously, which increases convenience and reduces time spent on these tasks. However, problems can arise in the security systems associated with these smart devices; security may be compromised when there are loopholes or human mistakes. When security credentials are lost, overall security can also be lost. This is because smart technology is made up of plenty of devices that are integrated with Internet of Things (IoT) technology and the cloud. This environment can introduce many security issues, as discussed in this text. Blockchain is a promising technology that operates in a decentralized environment to protect devices and the data collected by devices from security and privacy issues by using wireless communication technology. Blockchain-enabled IoT can be used to achieve end-to-end security. Blockchain technology is already used in wireless sensor/communication networks to estimate and predict house data and civil structures. IoT-integrated innovative applications like smart homes present unique security and privacy challenges. Scalability is the main problem as the current centralized IoT platforms have message routing mechanisms that create a bottleneck in scaling up too many devices used in IoT. As many devices are participating in generating data, such a setup may also be subjected to Distributed Denial of Service (DDoS) attacks. Lack of data standards is another cause of concern as it leads to interoperability problems. Blockchain technology for IoT and wireless communications offers a promising solution for smart devices. These technologies can provide end-to-end security and overcome the aforementioned problems. The usage of open-standard distributed IoT solutions can solve many problems that are associated with centralized approaches. Blockchain technology is nothing but a distributed ledger of transactions. It offers direct communication to connected devices. Such devices collect data, and all legitimate participants can access said data. Thus, decentralized blockchain networks can provide improved security for IoT-based solutions.
This book presents the technologies that empower edge intelligence, along with their use in novel IoT solutions. Specifically, it presents how 5G/6G, Edge AI, and Blockchain solutions enable novel IoT-based decentralized intelligence use cases at the edge of the cloud/edge/IoT continuum. Emphasis is placed on presenting how these technologies support a wide array of functional and non-functional requirements spanning latency, performance, cybersecurity, data protection, real-time performance, energy efficiency, and more. The various chapters of the book are contributed by several EU-funded projects, which have recently developed novel IoT platforms that enable the development and deployment of edge intelligence applications based on the cloud/edge paradigm. Each one of the projects employs its own approach and uses a different mix of networking, middleware, and IoT technologies. Therefore, each of the chapters of the book contributes a unique perspective on the capabilities of enabling technologies and their integration in practical real-life applications in different sectors. The book is structured in five distinct parts. Each one of the first four parts focuses on a specific set of enabling technologies for edge intelligence and smart IoT applications in the cloud/edge/IoT continuum. Furthermore, the fifth part provides information about complementary aspects of next-generation IoT technology, including information about business models and IoT skills. Specifically: The first part focuses on 5G/6G networking technologies and their roles in implementing edge intelligence applications. The second part presents IoT applications that employ machine learning and other forms of Artificial Intelligence at the edge of the network. The third part illustrates decentralized IoT applications based on distributed ledger technologies. The fourth part is devoted to the presentation of novel IoT applications and use cases spanning the cloud/edge/IoT continuum. The fifth part discusses complementary aspects of IoT technologies, including business models and digital skills.
This book constitutes the proceedings of the International Conference on Internet of Things, ICIOT 2018, held in Seattle, WA, USA, in June 2018. The 13 full papers and 1 short paper presented in this volume was carefully reviewed and selected for inclusion in this book. The contributions are organized in topical sections named: Research Track – Architecture; Research Track – Smart IoT; Application and Industry Track; and Short Paper Track. They deal with research and application innovations in the internet of things services.
This book explores recent advances in the Internet of things (IoT) via advanced technologies and provides an overview of most aspects which are relevant for advance secure, distributed, decentralized blockchain technology in the Internet of things, their applications, and industry IoT. The book provides an in-depth analysis of the step-by-step evolution of IoT to create a change by enhancing the productivity of industries. It introduces how connected things, data, and their communication (data sharing) environment build a transparent, reliable, secure environment for people, processes, systems, and services with the help of blockchain technology.