An Intelligent Sustainable Decentralized Trust Management Approach for Privacy-Preserving Smart Grid Communication Networks

Abstract

Smart grid communication networks are built from millions of sensors, smart meters and Internet of Things (IoT) devices that communicate with each other in real time, sharing valuable information about how energy is being used, what is happening on the grid and instructions for controlling it. The centralised trust management systems for authentication of devices and integrity of data raise significant privacy concerns, lead to single points of failure and require a lot of computational power. The traditional public-key infrastructure (PKI) and certificate based solutions are expensive, not scalable and do not scale to changes in the grid. These limitations are overcome by the Intelligent Sustainable Decentralized Trust Management Approach (ISDTM-SG) for privacy-preserving smart grid communication networks, proposed in this paper. This framework combines a lightweight distributed ledger system based on blockchain for storing immutable trust records, a federated learning approach to enhance anomaly detection without data sharing, a differential privacy feature to safeguard the energy consumption patterns, and a proof-of-stake consensus mechanism tailored for edge devices with limited resources. A reputation-scoring system that adjusts trust scores in real-time, as a function of energy balancing and behavioral history. Experimental results show that the proposed trust verification mechanism can reduce the latency of trust verification by 58.42%, reduce energy overhead by 64.37%, preserve privacy by 98.56%, detect attacks with 95.83%, and scale well with the numbers of smart meters and time (12,500 smart meters and 18 months). The proposed framework is found to be much more decentralized, private, energy-efficient and resilient than the centralized PKI and traditional blockchain and non-privacy-aware trust models do for next-generation smart grid communications.