REMODT: Reputation-Driven Efficient Many-to-One Data Trading Based on Blockchain

Existing data trading methods are mostly one-to-one trading models, which generate a large number of trading requests in multiseller scenarios. In addition, existing methods generally lack a comprehensive reputation mechanism and do not build protective measures against collusive attacks, resulting in multiple challenges in terms of efficiency and security in data trading. To address this issue, this article proposes a many-to-one data trading method named REMODT. This method designs a new type of data trading scheme that simplifies the trading process in a multiseller scenario and significantly improves trading efficiency. To ensure data security and privacy in the trading process, this article proposes an improved proxy re-encryption algorithm. In addition, this article also designs a new reputation mechanism that not only quantifies user reputation but also effectively curbs collusive attacks. The experimental results show that in a scenario with ten sellers and each seller selling ten pieces of data, compared with the latest one-to-one and one-to-many data trading methods, REMODT’s running time is reduced by 82% and 48%, and its gas consumption is reduced by 83% and 36%.