Hadoop云平台用户动态访问控制模型

doi:10.11959/j.issn.1000-436x.2017142

Abstract

Abstract:

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.

Key words: cloud platform, Hadoop, user behavior, access control, parallel command sequence learning

CLC Number:

TP393

Hong-yu YANG,Ling-xian MENG. Hadoop cloud platform user dynamic access control model[J]. Journal on Communications, 2017, 38(9): 9-17.

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References 12

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参数	取值
行为检测阈值x	0.4
行为评估基准值w	0.5
异常行为调节参数θ	0.4
初始行为评估值T_s	5
滑窗长度L	100
推荐评估值V_r	2
当前行为权重α	0.6
历史行为权重β	0.3
推荐评估值权重γ	0.1
阈值T_d	4.5

分类方法	异常行为检测率	异常行为误报率	时间/s
朴素贝叶斯	84.46%	7.12%	49.38
马尔可夫链模型	88.24%	1.24%	91.85
共生矩阵	90.02%	1.16%	201.23
PCSL	87.59%	1.33%	3.42

平台	操作	速率/(MB·s^-1)
	HDFS读	41.426
原Hadoop平台	HDFS写	20.562
	MapReduce WordCount	0.415
	HDFS读	39.859
部署DACUBA的Hadoop平台	HDFS写	19.632
	MapReduce WordCount	0.393

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Hadoop cloud platform user dynamic access control model

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