Hadoop云平台用户动态访问控制模型

摘要

In order to solve the problem that Hadoop cloud platform could not dynamically control user access request, a Hadoop cloud dynamic access control model based on user behavior assessment (DACUBA) was proposed. The model first collected the user instruction sequence in real time and the user behavior contour was obtained by parallel command sequence learning (PCSL). Then the global K model was established by using the forward profile, the subsequent se-quence was classified and the classification results were evaluated. The evaluation results were combined with the im-proved Hadoop access control mechanism to make the cloud platform users' access rights change dynamically with their own behaviors. Experimental results demonstrate that the model algorithm is effective and the dynamic access control mechanism is feasible.%为解决Hadoop云平台无法动态控制用户访问请求的问题,提出一种基于用户行为评估的Hadoop云平台动态访问控制(DACUBA,dynamic access control based on user behavior assessment)模型.该模型首先实时收集用户指令序列,通过并行指令序列学习(PCSL,parallel command sequence learning)获取用户行为轮廓.然后利用前向轮廓建立全局K模型,对后续行为序列进行分类并对分类结果进行评估.随后将评估结果与改进Hadoop访问控制机制结合,使云平台用户的访问权限随自身行为动态改变.最后通过实验验证了模型算法的有效性和动态访问控制机制的可行性.