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Automatic generation of Attribute-Based Access Control Policies from Natural Language Documents

Computers, Materials & Continua 2024年第9期80卷 3881-3902页

作者： Fangfang Shan Zhenyu Wang Mengyao Liu Menghan Zhang College of Computer Zhongyuan University of TechnologyZhengzhou450007China Henan Key Laboratory of Cyberspace Situation Awareness Zhengzhou450001China

In response to the challenges of generating Attribute-Based Access Control(ABAC)policies,this paper proposes a deep learning-based method to automatically generate ABAC policies from natural language *** method is aimed at organizations such as companies and schools that are transitioning from traditional access control models to the ABAC *** manual retrieval and analysis involved in this transition are inefficient,prone to errors,and *** organizations have high-level specifications defined for security policies that include a set of access control policies,which often exist in the form of natural language *** this rich source of information,our method effectively identifies and extracts the necessary attributes and rules for access control from natural language documents,thereby constructing and optimizing access control *** work transforms the problem of policy automation generation into two tasks:extraction of access control statements andmining of access control ***,the Chat General Language Model(ChatGLM)isemployed to extract access control-related statements from a wide range of natural language documents by constructing unique prompts and leveraging the model’s In-Context Learning to contextualize the ***,the Iterated Dilated-Convolutions-Conditional Random Field(ID-CNN-CRF)model is used to annotate access control attributes within these extracted statements,including subject attributes,object attributes,and action attributes,thus reassembling new access control *** results show that our method,compared to baseline methods,achieved the highest F1 score of 0.961,confirming the model’s effectiveness and accuracy.

关键词： Access control policy generation natural language deep learning

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