In the digital era, the challenges of data sovereignty and the conflict between personal data privacy protection and efficient access are becoming more pronounced. As a critical foundational support for resolving this contradiction, the digital identity framework holds significant research values. Based on a review of the research and development trends in cross-border digital identity authentication models, this study proposes a decentralized, distributed framework for cross-border identity authentication. The framework incorporates a data classification and grading strategy, and features three core components: a blockchain-based decentralized identity management mechanism, a universal certification pool model for dynamic data attribute classification and grading, and privacy protection and access control strategies. These components are designed to overcome the trust and compliance issues inherent in traditional centralized models in cross-border scenarios. Furthermore, this study delves into the application challenges of the cross-border digital identity authentication framework, such as the efficiency and accuracy of attribute association and heterogeneous grading, and the strategic interaction of trust boundaries for attribute authorization between cross-border parties. It refines corresponding solutions from the perspectives of application encapsulation of the authentication framework through application programming interface (API) models, evaluation criteria for the authentication framework, and implementation pathways. The proposed framework not only provides practical references for cross-border digital identity authentication but also offers new technical insights and implementation pathways for establishing unified standards and security protocols for cross-border data flow.