| 基于突变级数的网络流量异常检测 |
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| 引用本文： | 熊伟,胡汉平,王祖喜,杨越. 基于突变级数的网络流量异常检测[J]. 华中科技大学学报(自然科学版), 2011, 0(1): 28-31 |
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| 作者姓名： | 熊伟 胡汉平 王祖喜 杨越 |
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| 作者单位： | 华中科技大学图像识别与人工智能研究所;中南民族大学计算与实验中心; |
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| 基金项目： | 国家自然科学基金资助项目(60773192) |
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| 摘 要： | 针对网络流量发生异常时产生的突变特征,提出了一种基于突变级数的网络流量的异常检测方法.该方法首先计算网络流量的特征量,选择其中能显著性反映网络流量自相似性、非线性、非平稳性及复杂的动力学结构特性的特征量;然后将其作为突变理论的控制变量,利用蝴蝶突变模型的突变级数对网络流量异常进行检测.实验结果表明该方法具有较高的检测率和较低的误检率.
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| 关 键 词： | 异常检测 网络流量 特征选择 突变级数 检测率 误检率 |
Network traffic anomaly detection method based on catastrophe progression |
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| Xiong Wei, Hu Hanping Wang Zuxi Yang Yue. Network traffic anomaly detection method based on catastrophe progression[J]. JOURNAL OF HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY.NATURE SCIENCE, 2011, 0(1): 28-31 |
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| Authors: | Xiong Wei Hu Hanping Wang Zuxi Yang Yue |
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| Affiliation: | Xiong Wei1,2 Hu Hanping1 Wang Zuxi3 Yang Yue1(1 Institute of Pattern Recognition and Artificial Intelligence,Huazhong University of Science and Technology,Wuhan 430074,China,2 Center of Computing and Experimenting,South Central University for Nationalities,Wuhan 430079,China) |
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| Abstract: | Aimed at the catastrope characteristic when there are anomalies of network traffic happened,a network traffic anomaly detection approach based on the catastrophe progression theory was proposed.Some features of network traffic were calculated.The features significantly reflecting the self-similarity,non-linear,non-stationary nature and complexity of the dynamic structure of network traffic were chosen as the control variables of catastrophe theory.Then we used the catastrophe progression corresponding to th... |
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| Keywords: | anomaly detection network traffic feature selection catastrophe progression positive detection rate false alarm rate |
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