A Fine-Grained Access Control Method Based on Role Permission Management

In order to ensure the security of data in power systems, it is necessary to establish a complete data protection system. This paper proposes an innovative access control technology framework based on fine-grained data access control technology and role-based access control management. This framework not only embeds a neural network model, but also introduces context-based information to implement scenario-based access control, making access permissions more precise and flexible. The fine-grained access control technology framework utilizes a data classification model and a hierarchical model, and can sort sensitive data in the directory based on desired classification results, characteristics, and preset data levels. Finally, access matching algorithms can be built based on the required roles and data to achieve rapid matching of hierarchical data and different roles. In summary, the fine-grained access control technology framework based on role-based access control management proposed in this article is a very valuable innovation. It cannot only better protect sensitive data in power systems, but also more accurately and flexibly meet user requirements in terms of access control. The data security protection system established based on this technical framework can effectively respond to different requirements, including different levels and scenarios, and improve the security of the system.