Research on Credit Assessment Model of Blockchain Technology in Data Security and Privacy Protection

Abstract

This study constructs an innovative credit assessment model, combining blockchain technology with a credit scoring system to focus on solving data security and privacy protection issues. The model achieves security and transparency in the credit assessment process by designing a series of advanced algorithms and system architectures. The model uses zero-knowledge proof technology to allow users to verify their identities without revealing specific data information, thereby ensuring that privacy is not leaked. The model also introduces a distributed storage mechanism to store data on multiple nodes in a dispersed manner, preventing single point failures and improving the immutability of data. This study verifies the superiority of the model in data processing speed, assessment accuracy and system security through simulation tests. The results show that the accuracy of the model is about 15% higher than that of traditional methods, and the risk of data leakage is significantly reduced by about 20%. The blockchain credit assessment model achieves efficient and reliable credit assessment while meeting user privacy protection, providing a reference with practical value for the construction of the future credit system.