Abstract

In the era of big data, facilitating efficient data flow is of paramount importance. Governments and enterprises worldwide have been investing in the big data industry, promoting data sharing and trading. However, existing data trading platforms often suffer from issues like privacy breaches, single points of failure, data tampering, and non-transparent transactions due to their reliance on centralized servers. To address these challenges, blockchain-based big data transaction models have been proposed. However, these models often lack system integrity and fail to fully meet user requirements while ensuring adequate security. To overcome these limitations, this paper presents an Ethereum-based big data trading model that establishes a comprehensive and secure trading system. The model aims to provide users with more convenient, secure, and professional services. Through the utilization of smart contracts, users can efficiently match data and negotiate prices online while ensuring secure data delivery through encryption technologies. Additionally, the model introduces a trusted third-party entity that offers professional data evaluation services and actively safeguards user data ownership in the event of disputes. The implementation of the model includes the development of smart contracts and the necessary machine learning code, followed by rigorous testing and validation. The experimental results validate the effectiveness and reliability of our proposed model, demonstrating its potential to ensure effective and secure big data trading.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.