Open Access

ARTICLE

Research on Quantification Mechanism of Data Source Reliability Based on Trust Evaluation

Gaoshang Lu^#, Fa Fu^#,*, Zixiang Tang

School of Computer Science and Technology, Hainan University, Haikou, 570228, China

* Corresponding Author: Fa Fu. Email:
# These authors contributed equally to this work

Computers, Materials & Continua 2025, 83(3), 4239-4256. https://doi.org/10.32604/cmc.2025.062556

Received 20 December 2024; Accepted 10 March 2025; Issue published 19 May 2025

Abstract

In the data transaction process within a data asset trading platform, quantifying the trustworthiness of data source nodes is challenging due to their numerous attributes and complex structures. To address this issue, a distributed data source trust assessment management framework, a trust quantification model, and a dynamic adjustment mechanism are proposed. The model integrates the Analytic Hierarchy Process (AHP) and Dempster-Shafer (D-S) evidence theory to determine attribute weights and calculate direct trust values, while the PageRank algorithm is employed to derive indirect trust values. The direct and indirect trust values are then combined to compute the comprehensive trust value of the data source. Furthermore, a dynamic adjustment mechanism is introduced to continuously update the comprehensive trust value based on historical assessment data. By leveraging the collaborative efforts of multiple nodes in the distributed network, the proposed framework enables a comprehensive, dynamic, and objective evaluation of data source trustworthiness. Extensive experimental analyses demonstrate that the trust quantification model effectively handles large-scale data source trust assessments, exhibiting both strong trust differentiation capability and high robustness.

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Keywords

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