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The application of Intelligent Internet of Things (IIoT) in constructing distribution station areas strongly supports platform transformation, upgrade, and intelligent integration. The sensing layer of IIoT comprises the edge convergence layer and the end sensing layer, with the former using intelligent fusion terminals for real-time data collection and processing. However, the influx of multiple low-voltage in the smart grid raises higher demands for the performance, energy efficiency, and response speed of the substation fusion terminals. Simultaneously, it brings significant security risks to the entire distribution substation, posing a major challenge to the smart grid. In response to these challenges, a proposed dynamic and energy-efficient trust measurement scheme for smart grids aims to address these issues. The scheme begins by establishing a hierarchical trust measurement model, elucidating the trust relationships among smart IoT terminals. It then incorporates multidimensional measurement factors, encompassing static environmental factors, dynamic behaviors, and energy states. This comprehensive approach reduces the impact of subjective factors on trust measurements. Additionally, the scheme incorporates a detection process designed for identifying malicious low-voltage end sensing units, ensuring the prompt identification and elimination of any malicious terminals. This, in turn, enhances the security and reliability of the smart grid environment. The effectiveness of the proposed scheme in pinpointing malicious nodes has been demonstrated through simulation experiments. Notably, the scheme outperforms established trust metric models in terms of energy efficiency, showcasing its significant contribution to the field.

Enhancing Energy Efficiency with a Dynamic Trust Measurement Scheme in Power Distribution Network