现代电子技术2025，Vol.48Issue(16)：50-54,5.DOI:10.16652/j.issn.1004-373x.2025.16.009
结合深度学习和自适应的业务动态访问控制研究及应用分析
Research and application analysis of business dynamic access control based on deep learning and adaptive technology
摘要
Abstract
In order to solve the problem that traditional access control means are difficult to meet the requirements of dynamic assessment and response,a method of zero-trust security access integrating deep learning and adaptive dynamic access control(DA-ZeroTrust)is proposed.The vectorized representation of user behaviors is constructed and the temporal dependency relationships of interaction sequences are explored,so as to realize the continuous assessment of user behaviors and the detection of abnormal user identities.The Markov decision process is used to evaluate the value of access behavior,so as to realize the adaptive allocation of dynamic access control permissions.The experimental results show that this method can effectively overcome key technical difficulties such as user encoding,semantic feature extraction and abnormal behavior detection,and is able to quickly detect and respond to abnormal behaviors.关键词
访问控制/零信任/深度学习/自适应动态访问控制/异常检测/马尔科夫决策过程/访问行为价值Key words
access control/zero trust/deep learning/adaptive dynamic access control/anomaly detection/Markov decision process/access behavior value分类
信息技术与安全科学引用本文复制引用
李玮,张金金,张肖艳..结合深度学习和自适应的业务动态访问控制研究及应用分析[J].现代电子技术,2025,48(16):50-54,5.基金项目
陕西省重点研发计划资助项目(2023-YBGY-227) （2023-YBGY-227）
陕西省自然科学基础研究计划资助项目(2023-JC-QN-0705) （2023-JC-QN-0705）
