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This book reviews research works in recent trends in blockchain, AI, and Digital Twin based IoT data analytics approaches for providing the privacy and security solutions for Fog-enabled IoT networks. Due to the large number of deployments of IoT devices, an IoT is the main source of data and a very high volume of sensing data is generated by IoT systems such as smart cities and smart grid applications. To provide a fast and efficient data analytics solution for Fog-enabled IoT systems is a fundamental research issue. For the deployment of the Fog-enabled-IoT system in different applications such as healthcare systems, smart cities and smart grid systems, security, and privacy of big IoT data and IoT networks are key issues. The current centralized IoT architecture is heavily restricted with various challenges such as single points of failure, data privacy, security, robustness, etc.This book emphasizes and facilitates a greater understanding of various security and privacy approaches using the advances in Digital Twin and Blockchain for data analysis using machine/deep learning, federated learning, edge computing and the countermeasures to overcome these vulnerabilities.
Doctoral Thesis / Dissertation from the year 2021 in the subject Computer Science - IT-Security, grade: A, , language: English, abstract: Blockchain is an emerging technology, leveraged with features of decentralization, tamper-proof records storage model based on a Peer-to-Peer architecture. It has been mostly applied in financial applications, and extended to various applications, viz., healthcare, supply-chain, and identity management. However, privacy, security, and scalability are the key challenges in blockchain-based applications that immensely limit the extensive adoption of these extended applications. The work in this thesis addresses the aforementioned challenges, while preserving better privacy, security, and scalability in blockchain-based applications. We propose access control techniques to facilitate better privacy, security in the blockchain network and improve scalability off-chain storage model. First, we propose an access control technique to preserve privacy across the blockchain network such that authorized peers can access the resources. Initially, the access control technique is designed for resource privacy. Further, we extend the policy to preserve privacy in blockchain network by categorizing both peers and resources. In this thesis, we also address another important problem, i.e., scalability in blockchain network while storing large size of data in secure off-chain storage. We use a secure distributed off-chain storage model to address the problem of scalability, based on the structure of the blockchain network. Lastly, we propose two-level of privacy preservation approach in blockchain network, while maintaining the scalability in the network. The proposed approach uses BlockCloud-BlockFog structure for deployment and IPFS-based off-chain storage model for large size data storage. All the proposed frameworks are evaluated using real-world data sets.
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