Institution Attribute Mining Technology for Access Control Based on Hybrid Capsule Network  

作　　者：Aodi Liu Xuehui Du Na Wang Xiangyu Wu 

机构地区：[1]Henan Province Key Laboratory of Information Security,Information Engineering University,Zhengzhou,450000,China

出　　处：《Computers, Materials & Continua》2025年第4期1495-1513,共19页计算机、材料和连续体(英文)

基　　金：supported by National Natural Science Foundation of China(No.62102449).

摘　　要：Security attributes are the premise and foundation for implementing Attribute-Based Access Control(ABAC)mechanisms.However,when dealing with massive volumes of unstructured text big data resources,the current attribute management methods based on manual extraction face several issues,such as high costs for attribute extraction,long processing times,unstable accuracy,and poor scalability.To address these problems,this paper proposes an attribute mining technology for access control institutions based on hybrid capsule networks.This technology leverages transfer learning ideas,utilizing Bidirectional Encoder Representations from Transformers(BERT)pre-trained language models to achieve vectorization of unstructured text data resources.Furthermore,we have designed a novel end-to-end parallel hybrid network structure,where the parallel networks handle global and local information features of the text that they excel at,respectively.By employing techniques such as attention mechanisms,capsule networks,and dynamic routing,effective mining of security attributes for access control resources has been achieved.Finally,we evaluated the performance level of the proposed attribute mining method for access control institutions through experiments on the medical referral text resource dataset.The experimental results show that,compared with baseline algorithms,our method adopts a parallel network structure that can better balance global and local feature information,resulting in improved overall performance.Specifically,it achieves a comprehensive performance enhancement of 2.06%to 8.18%in the F1 score metric.Therefore,this technology can effectively provide attribute support for access control of unstructured text big data resources.

关 键 词：Access control ABAC model attribute mining capsule network deep learning 

分 类 号：TP309[自动化与计算机技术—计算机系统结构]