The proliferation of diverse entities within distribution network has led to an increase in the scale and complexity of data asset interactions

exacerbating security risks

such as unauthorized access

data tampering

and forgery. In response to these challenges

this study introduces a novel framework that enhances the protection of data assets. It incorporates a multi-dimensional knowledge graph(MDKG) to refine access control and overcome current limitations by integrating a comprehensive set of data asset attributes

roles

policies

and permissions. This approach fosters the development of a nuanced and adaptable access-control mechanism. Furthermore

the framework integrates multiple topology(MTP)for holistic security risk detection

leveraging attention mechanisms

and cross-fusion to adapt to the dynamic data security landscape. Empirical evaluations affirm the effectiveness of MDKG-based access control

whereas comparative experiments demonstrate the superiority of the MTP-based security risk model over existing models. The framework was proven to be effective in countering security risks. This study provides innovative perspectives on data asset protection and establishes a solid foundation for the advancement of smart grid technology.