ABSTRACT
Blockchain technology has attracted great attention from academia and industry for the past 10 years. One of the major reason behind this attention is the decentralised nature of blockchain, which enhances trust and the security of users’ data. Researchers are implementing the blockchain concept to almost every field of life, and blockchain has provided numerous benefits that were beyond imagination a decade ago. However, the computationally complex nature of blockchain restricts its usage in some applications in which devices do not have enough computational power, such as the Internet of Things (IoT) and smart grid. In such applications, edge computing came as a saviour and provided a platform for these applications to use the benefits from the modern technology of blockchain. Integrating blockchain with edge computing ensures enhancement in storage, access, and computational capabilities. Blockchain-based edge computing provides a large network in which IoT devices can use a secure decentralised ledger of blockchain without worrying about their computational complexity restrictions. One such application is modern smart grid advanced metering infrastructure (AMI) networks, in which every smart meter will act as blockchain node and will be connected with each other and with a main power grid. This integration will allow smart meters to make timely reports of their data to the smart grid utility, which can in turn use the data for various purposes without compromising the data security. Although, this decentralised integration solved many issues, the issue of privacy leakage is still present because of the transparent nature of blockchain. The data of smart meter users (such as instantaneous electricity usage) will be available on a decentralised distributed ledger, which causes serious concerns about users’ privacy. In this chapter, we propose a differentially private decentralised on-demand electricity reporting strategy in which private data of smart meter users will be protected using an advanced perturbation technique to overcome this issue. In this approach, every user will be able to share real-time data to a smart grid utility without risking the loss of privacy. Performance evaluation of our proposed strategy ensures that the data of smart meter users is successfully protected from all kinds of adversaries.
