基于用户行为评估的Hadoop云平台动态访问控制

Hadoop Cloud Platform Dynamic Access Control Based on User Behavior Assessment

为解决现有Hadoop云平台访问控制缺乏动态性的问题,提出一种基于用户行为评估的Hadoop云平台动态访问控制模型(DACUBA).该模型采用指令序列学习(CSL)算法从用户指令序列中提取用户行为模式,利用全局模式库对用户行为进行分类并对分类结果进行行为评估,然后将评估值应用于Hadoop云平台的访问控制机制中实现动态访问控制.验证实验结果证明了DACUBA的有效性,与其他方法相比,该方法对云请求的访问控制效率较高,且稳定性较好.

In order to solve the problem that the access control model of the existing Hadoop cloud platform lacks dynamic mechanism,a dynamic access control model based on user behavior assessment（DACUBA）was proposed for Hadoop cloud platform.In this model,a command sequence learning（CSL）algorithm was used to extract user behavior patterns from user instruction sequence,the global pattern library was used to classify user behavior and conduct behavioral assessment of user behavior classification.Then the evaluation value was applied to the access control mechanism of Hadoop cloud platform to implement dynamic access control.The experimental results verify that DACUBA is effective,and compared with other methods,this method has higher efficiency and better stability for cloud request access control.