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 sequence was classified and the classification results were evaluated.The evaluation results were combined with the improved 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.
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