Özet:

Abstract Energy trading helps buyers and sellers trade energy in today’s dynamic energy markets. However, protecting sensitive energy trade data has become a priority as digital platforms become more important. Traditional encryption methods may not be enough for energy trading applications. This study proposes using homomorphic encryption to solve these problems. Energy trade data is protected by the suggested encryption technique, which uses the RSA algorithm, OAEP padding scheme, and SHA256 hash algorithm. Python is used to create a simulation framework to test the suggested strategy. Random energy needs, supply, and buyer and seller prices are produced to simulate energy trading transactions. Homomorphic encryption is secure and efficient, as shown through simulations. The research investigates the scheme’s performance using homomorphic techniques to reduce computing overheads. The simulation code also assures correctness and reliability throughout the evaluation. Energy trading system buyers’ entire value is visualised using bar charts. The results derived from the simulations demonstrate the efficacy of the proposed methodology. The homomorphic encryption scheme effectively maintains the confidentiality of sensitive trading data throughout its transmission and storage. The encrypted data is securely stored and shared within the blockchain-based GreenTrade platform, establishing a reliable and trustworthy environment for participants engaged in energy trading. The assessment of the system’s performance showcases the effectiveness of the encryption scheme, rendering it a feasible resolution for energy trading scenarios in real-world scenarios. This research article thoroughly investigates a unique hybrid strategy for safe and efficient energy trading employing homomorphic encryption. The suggested encryption technique addresses energy trade data security and privacy. The simulation findings demonstrate the approach’s viability and promise to improve energy trading security and privacy. The research advances energy trading by using modern cryptography.

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