This invention provides an RBAC+ABAC-supported
access control method for AI knowledge bases, belonging to the field of AI
knowledge base technology. This invention employs a
gradient boosting decision tree and a
Bloom filter to construct a simplified
decision model. An optimization
algorithm based on thermodynamic entropy finds the policy configuration with the
minimum entropy value through
simulated annealing, eliminating rule conflicts and simplifying the logical structure. During vector retrieval, the permission encoding vector and
semantic vector are concatenated to form a joint vector to construct a permission-aware index. During answer generation, a permission context
fingerprint is attached, and secondary propagation of permissions is verified through a permission re-
verification gateway. Operation logs are recorded using a
hash chain structure to ensure the immutability of audit
traceability. This invention solves the technical problem that AI knowledge bases cannot simultaneously guarantee the efficiency of permission decisions and the
maintainability of policy rules when performing fine-grained
access control.