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What is Auto-Generating ABAC Policies from Text about?

This paper presents a deep learning-based method for automatically generating Attribute-Based Access Control (ABAC) policies from natural language documents, addressing inefficiencies in traditional access control models. The method employs the Chat General Language Model (ChatGLM) for extracting access control statements and the ID-CNN-CRF model for annotating access control attributes, achieving a high F1 score of 0.961 in experiments. This approach aims to streamline the transition to ABAC by leveraging

Author

Bilal Ahmed

Language

EN