Smart grid stands as both the cornerstone of the modern energy system and the pivotal technology for addressing energy-related challenges. Advanced Metering Infrastructure constitute a critical component within the smart grid ecosystem, providing real-time energy consumption data to power utility companies. Advanced Metering Infrastructure enables these companies to make timely and accurate decisions. Hence, the issue of data security pertaining to Advanced Metering Infrastructure assumes profound significance. Presently, Advanced Metering Infrastructure data confronts challenges associated with centralized data storage, rendering it susceptible to potential cyberattacks. Moreover, with the burgeoning number of electricity consumers, the resultant data volumes have swelled considerably. Consequently, the transmission of this data becomes intricate and its efficiency is compromised. To address these issues, this paper presents a lightweight blockchain data aggregation scheme. By integrating fog computing and cloud computing, a three-tier blockchain-based architecture is devised. Initially, digital signatures are employed to ensure the validity and integrity of user data. The innate attributes of blockchain technology are harnessed to safeguard the security of electricity energy data. Through secondary data aggregation, the privacy-sensitive user data is efficiently compressed and subsequently integrated into the blockchain, thereby mitigating the storage pressure on the blockchain and enhancing data transmission efficiency. Ultimately, through rigorous theoretical analysis and simulated experimentation, the paper demonstrates that, in comparison to existing methodologies, lightweight blockchain data aggregation scheme exhibits heightened security. Additionally, lightweight blockchain data aggregation scheme holds a competitive advantage in terms of computational and communication costs.
CITATION STYLE
Tian, H., Zheng, N., & Jian, Y. (2023). Advanced Metering Infrastructure Data Aggregation Scheme Based on Blockchain. International Journal of Advanced Computer Science and Applications, 14(11), 265–273. https://doi.org/10.14569/IJACSA.2023.0141126
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