A Blockchain-based Privacy-Preserving Matching Scheme for Power Data

The current mode of power data trading heavily re-lies on web pages as the conventional mediation method. However, dishonest parties in trading may intentionally resell the dataset of the power grid company, or the grid company may be unable to determine what the buyer has done with the power data, thereby compromising the privacy of power users. Therefore, enhancing efficiency and privacy while ensuring trading security and data reliability is a challenging task in the field of power data trading. To address the issue of whether the power data provided by sellers aligns with the requirements of buyers in power data trading, a blockchain-based supply-demand consistency privacy-preserving matching scheme (BPMS) is proposed. The scheme leverages attribute-based searchable encryption (ABSE) and linear secret sharing scheme-based matching strategy to create a matching environment that adheres to privacy protection requirements, enabling consistent alignment of supply and demand while safe-guarding the privacy of power users. Subsequently, by equipping the blockchain-based power data trading platform (BDTP) with public and private keys, it ensures that matching services can only occur within the specified platform. The construction of the blockchain enables the storage of matching information on-chain for future queries and traceability. Furthermore, the BPMS also implements access control on the buyer's data processing tasks. By utilizing LSSS-based ciphertext policy attribute-based encryption (CP-ABE), it allows the seller to decrypt and obtain insights into the processing task taken by the buyer with the power data after successful matching and meeting specific attribute criteria. Finally, the scheme undergoes analysis and performance evaluation, demonstrating its feasibility and superiority.