Blockchain intelligence empowered secure uncertainty management in IoT assisted smart grids

Abstract The recent advances in renewable energy sources impose a greater need for smart grid. However, the process of power generation, distribution and consumption across smart grids are highly complex. Conventional systems are more prone to various security attacks and become a single point of failure during many instances. This paper proposes a blockchain-based decentralised multiparty learning system to ensure the stability of the smart grid while enhancing security and efficiency measures through blockchain. Simulations were conducted using a power grid dataset from Kaggle, and observations were made considering various factors. From the experiment, it was noted that the proposed approach takes an average of 25 ms to read the data across the blocks and approximately 4 s to generate a new block. Moreover, concerning the addition of a higher number of intelligent terminals, the proposed approach consumes only 70% of the energy required by conventional methods to perform the task. The prediction and classification accuracy of the proposed system is also analysed, showing a measure of 98% accuracy.

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Publication Details

Journal
Cluster Computing
Published
2026-02-16
DOI
https://doi.org/10.1007/s10586-026-05984-3
Primary Topic
Smart Grid Security and Resilience
Type
article
Field-Weighted Citation Impact
0.00
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article

Blockchain intelligence empowered secure uncertainty management in IoT assisted smart grids

Alaa Khadidos, G. S. Tamizharasi, R. Sathiyaraj, K. P. Arjun et al.
Cluster Computing
Smart Grid Security and Resilience
article

Blockchain intelligence empowered secure uncertainty management in IoT assisted smart grids

Alaa Khadidos, G. S. Tamizharasi, R. Sathiyaraj, K. P. Arjun, Balamurugan Balusamy, Firoz Khan
article en

Abstract

Abstract The recent advances in renewable energy sources impose a greater need for smart grid. However, the process of power generation, distribution and consumption across smart grids are highly complex. Conventional systems are more prone to various security attacks and become a single point of failure during many instances. This paper proposes a blockchain-based decentralised multiparty learning system to ensure the stability of the smart grid while enhancing security and efficiency measures through blockchain. Simulations were conducted using a power grid dataset from Kaggle, and observations were made considering various factors. From the experiment, it was noted that the proposed approach takes an average of 25 ms to read the data across the blocks and approximately 4 s to generate a new block. Moreover, concerning the addition of a higher number of intelligent terminals, the proposed approach consumes only 70% of the energy required by conventional methods to perform the task. The prediction and classification accuracy of the proposed system is also analysed, showing a measure of 98% accuracy.

Cluster ComputingVol. 29(3)
King Abdulaziz University (SA), Ball State University (US), Shiv Nadar University (IN), CMR University (IN), Chitkara University (IN), Leeds Beckett University (GB), GITAM University (IN)
Affordable and clean energy
Openalex Percentile: Top 54%
Smart Grid Security and Resilience
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