Framework for Data Trust Using Block-chain Technology and Adaptive Transaction Validation

Abstract

The major obstacle limiting extensive data exchange is trust. Many data owners are unable to share their data due to the absence of transparent infrastructures for establishing data trust, while data consumers are concerned about the quality of the shared data. Data sharing is made easier by the data trust paradigm, which requires data users to be open about how they share and reuse their data. By using numerous parties to preserve agreement on an immutable record, blockchain technology suggests a distributed and transparent administration. With the use of blockchain technology, this article provides an end-to-end architecture for data trust that will improve reliable data exchange. The framework successfully handles access control, displays data provenance and activity tracking, and enhances data quality by evaluating input data sets. To assess the quality of the data, we provide an evaluation model that takes reputation, endorsement, and consistency into account.

We also provide an adaptive approach to calculating the estimated trust value-based number of transaction validators. By assuring the reliability and quality of the data at its source and its ethical and secure use in the end, the suggested data trust framework allays the worries of both data owners and consumers. A thorough experimental research reveals that the system being described can efficiently handle many transactions with little delay.