<p>Traditional smart grids face challenges such as low aggregation efficiency, high computation and communication costs, and difficulties in maintaining privacy and security during data aggregation. To address these issues, we propose a fog-assisted smart grid data aggregation scheme based on dual blockchain and improved stellar consensus protocol (ISCP). Firstly, based on the combination of cloud and fog architectures, dual blockchain and two-level data aggregation are designed to attain fine-grained data aggregation. Secondly, fuzzy algorithms are used to achieve efficient aggregation by grouping nodes with high data similarity. Finally, the ISCP consensus is designed, and a new committee consensus algorithm is introduced to enhance the system’s performance and security. Security analysis demonstrates that the scheme is existential unforgeability-chosen message attack (EUF-CMA) secure and can resist eavesdropping attack, active attack and collusion attack. Performance evaluation also shows that our scheme decreases the computational overhead by 35% on average and has better aggregation accuracy compared with similar solutions.</p>

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DBIA-DA: dual-blockchain and ISCP-assisted data aggregation for fog-enabled smart grid

  • Lihua Zhang,
  • Yi Yang,
  • Jiali Luo,
  • Wenbiao Wang,
  • Jinguang Gu

摘要

Traditional smart grids face challenges such as low aggregation efficiency, high computation and communication costs, and difficulties in maintaining privacy and security during data aggregation. To address these issues, we propose a fog-assisted smart grid data aggregation scheme based on dual blockchain and improved stellar consensus protocol (ISCP). Firstly, based on the combination of cloud and fog architectures, dual blockchain and two-level data aggregation are designed to attain fine-grained data aggregation. Secondly, fuzzy algorithms are used to achieve efficient aggregation by grouping nodes with high data similarity. Finally, the ISCP consensus is designed, and a new committee consensus algorithm is introduced to enhance the system’s performance and security. Security analysis demonstrates that the scheme is existential unforgeability-chosen message attack (EUF-CMA) secure and can resist eavesdropping attack, active attack and collusion attack. Performance evaluation also shows that our scheme decreases the computational overhead by 35% on average and has better aggregation accuracy compared with similar solutions.