| 基于动态阈值的网络异常检测 |
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| 引用本文： | 冯兴杰,焦文欢.基于动态阈值的网络异常检测[J].计算机工程与设计,2012,33(6):2182-2186. |
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| 作者姓名： | 冯兴杰 焦文欢 |
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| 作者单位： | 中国民航大学 计算机科学与技术学院,天津,300300 |
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| 基金项目： | 国家自然科学基金项目，民航局科技基金项目 |
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| 摘 要： | 基于Hurst指数进行异常检测的模型多采用固定阈值的方法,不能很好的适应动态变化的网络环境.针对该问题设计了一种基于动态阈值的检测方法,该方法在采用Hurst指数分析的基础上,通过EWMA和滑动窗口模型控制有效数据的个数并根据网络的变化动态调整检测阈值,提高了模型的检测能力.实验结果表明,在采用动态阈值进行DDOS异常检测时具有较高的检测率.
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| 关 键 词： | 网络异常检测 赫斯特指数 滑动窗口 指数平滑模型 小波系数方差 |
Network abnormality detection based on dynamic threshold |
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| FENG Xing-jie
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JIAO Wen-huan.Network abnormality detection based on dynamic threshold[J].Computer Engineering and Design,2012,33(6):2182-2186. |
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| Authors: | FENG Xing-jie JIAO Wen-huan |
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| Affiliation: | (School of Computer Science and Technology,Civil Aviation University of China,Tianjin 300300,China) |
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| Abstract: | Most anomaly detection model based on Hurst index use fixed threshold,but it doesn’t well adapt to the dynamic changing network.To sdve the problem,a dynamic threshold detection method is proposed.After using wavelet analysis in the Hurst value,according to changes in the network,it controls the number of valid data to dynamically adjust the threshold value based on sliding window and EWMA.Thus,the detection ability of the model is improved.Experimental results show that the method of dynamic thresholds have a higher detection rate in DDOS detection. |
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| Keywords: | network anomaly detections hurst exponent sliding window exponential smoothing model wavelet coefficients of variance |
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