Blockchain for secured IoT and D2D applications over 5G cellular networks : a thesis by publications presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer and Electronics Engineering, Massey University, Albany, New Zealand

Author's Declaration: "In accordance with Sensors, SpringerOpen, and IEEE’s copyright policy, this thesis contains the accepted and published version of each manuscript as the final version. Consequently, the content is identical to the published versions."The Internet of things (IoT) is in continuous development with ever-growing popularity. It brings significant benefits through enabling humans and the physical world to interact using various technologies from small sensors to cloud computing. IoT devices and networks are appealing targets of various cyber attacks and can be hampered by malicious intervening attackers if the IoT is not appropriately protected. However, IoT security and privacy remain a major challenge due to characteristics of the IoT, such as heterogeneity, scalability, nature of the data, and operation in open environments. Moreover, many existing cloud-based solutions for IoT security rely on central remote servers over vulnerable Internet connections. The decentralized and distributed nature of blockchain technology has attracted significant attention as a suitable solution to tackle the security and privacy concerns of the IoT and device-to-device (D2D) communication. This thesis explores the possible adoption of blockchain technology to address the security and privacy challenges of the IoT under the 5G cellular system. This thesis makes four novel contributions. First, a Multi-layer Blockchain Security (MBS) model is proposed to protect IoT networks while simplifying the implementation of blockchain technology. The concept of clustering is utilized to facilitate multi-layer architecture deployment and increase scalability. The K-unknown clusters are formed within the IoT network by applying a hybrid Evolutionary Computation Algorithm using Simulated Annealing (SA) and Genetic Algorithms (GA) to structure the overlay nodes. The open-source Hyperledger Fabric (HLF) Blockchain platform is deployed for the proposed model development. Base stations adopt a global blockchain approach to communicate with each other securely. The quantitative arguments demonstrate that the proposed clustering algorithm performs well when compared to the earlier reported methods. The proposed lightweight blockchain model is also better suited to balance network latency and throughput compared to a traditional global blockchain. Next, a model is proposed to integrate IoT systems and blockchain by implementing the permissioned blockchain Hyperledger Fabric. The security of the edge computing devices is provided by employing a local authentication process. A lightweight mutual authentication and authorization solution is proposed to ensure the security of tiny IoT devices within the ecosystem. In addition, the proposed model provides traceability for the data generated by the IoT devices. The performance of the proposed model is validated with practical implementation by measuring performance metrics such as transaction throughput and latency, resource consumption, and network use. The results indicate that the proposed platform with the HLF implementation is promising for the security of resource-constrained IoT devices and is scalable for deployment in various IoT scenarios. Despite the increasing development of blockchain platforms, there is still no comprehensive method for adopting blockchain technology on IoT systems due to the blockchain's limited capability to process substantial transaction requests from a massive number of IoT devices. The Fabric comprises various components such as smart contracts, peers, endorsers, validators, committers, and Orderers. A comprehensive empirical model is proposed that measures HLF's performance and identifies potential performance bottlenecks to better meet blockchain-based IoT applications' requirements. The implementation of HLF on distributed large-scale IoT systems is proposed. The performance of the HLF is evaluated in terms of throughput, latency, network sizes, scalability, and the number of peers serviceable by the platform. The experimental results demonstrate that the proposed framework can provide a detailed and real-time performance evaluation of blockchain systems for large-scale IoT applications. The diversity and the sheer increase in the number of connected IoT devices have brought significant concerns about storing and protecting the large IoT data volume. Dependencies of the centralized server solution impose significant trust issues and make it vulnerable to security risks. A layer-based distributed data storage design and implementation of a blockchain-enabled large-scale IoT system is proposed to mitigate these challenges by using the HLF platform for distributed ledger solutions. The need for a centralized server and third-party auditor is eliminated by leveraging HLF peers who perform transaction verification and records audits in a big data system with the help of blockchain technology. The HLF blockchain facilitates storing the lightweight verification tags on the blockchain ledger. In contrast, the actual metadata is stored in the off-chain big data system to reduce the communication overheads and enhance data integrity. Finally, experiments are conducted to evaluate the performance of the proposed scheme in terms of throughput, latency, communication, and computation costs. The results indicate the feasibility of the proposed solution to retrieve and store the provenance of large-scale IoT data within the big data ecosystem using the HLF blockchain

Blockchain and 6G-Enabled IoT

Ubiquitous computing turns into a reality with the emergence of the Internet of Things (IoT) adopted to connect massive numbers of smart and autonomous devices for various applications. 6G-enabled IoT technology provides a platform for information collection and processing at high speed and with low latency. However, there are still issues that need to be addressed in an extended connectivity environment, particularly the security and privacy domain challenges. In addition, the traditional centralized architecture is often unable to address problems associated with access control management, interoperability of different devices, the possible existence of a single point of failure, and extensive computational overhead. Considering the evolution of decentralized access control mechanisms, it is necessary to provide robust security and privacy in various IoT-enabled industrial applications. The emergence of blockchain technology has changed the way information is shared. Blockchain can establish trust in a secure and distributed platform while eliminating the need for third-party authorities. We believe the coalition of 6G-enabled IoT and blockchain can potentially address many problems. This paper is dedicated to discussing the advantages, challenges, and future research directions of integrating 6G-enabled IoT and blockchain technology for various applications such as smart homes, smart cities, healthcare, supply chain, vehicle automation, etc

IoT Big Data provenance scheme using blockchain on Hadoop ecosystem

Abstract The diversity and sheer increase in the number of connected Internet of Things (IoT) devices have brought significant concerns associated with storing and protecting a large volume of IoT data. Storage volume requirements and computational costs are continuously rising in the conventional cloud-centric IoT structures. Besides, dependencies of the centralized server solution impose significant trust issues and make it vulnerable to security risks. In this paper, a layer-based distributed data storage design and implementation of a blockchain-enabled large-scale IoT system are proposed. It has been developed to mitigate the above-mentioned challenges by using the Hyperledger Fabric (HLF) platform for distributed ledger solutions. The need for a centralized server and a third-party auditor was eliminated by leveraging HLF peers performing transaction verifications and records audits in a big data system with the help of blockchain technology. The HLF blockchain facilitates storing the lightweight verification tags on the blockchain ledger. In contrast, the actual metadata are stored in the off-chain big data system to reduce the communication overheads and enhance data integrity. Additionally, a prototype has been implemented on embedded hardware showing the feasibility of deploying the proposed solution in IoT edge computing and big data ecosystems. Finally, experiments have been conducted to evaluate the performance of the proposed scheme in terms of its throughput, latency, communication, and computation costs. The obtained results have indicated the feasibility of the proposed solution to retrieve and store the provenance of large-scale IoT data within the Big Data ecosystem using the HLF blockchain. The experimental results show the throughput of about 600 transactions, 500 ms average response time, about 2–3% of the CPU consumption at the peer process and approximately 10–20% at the client node. The minimum latency remained below 1 s however, there is an increase in the maximum latency when the sending rate reached around 200 transactions per second (TPS)