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OALib Journal期刊
ISSN: 2333-9721
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DDoS attack detection method based on Holder exponent
一种基于Holder指数的DDoS攻击检测方法*

Keywords: distributed denial of service(DDoS),self-similar,multi-fractal,Hurst parameter,Holder exponent
分布式拒绝服务
,自相似性,多重分形,Hurst参数,Holder指数

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Abstract:

Based on the fractal structure of the large-scale network traffic aggregation,analyzed the fractal feature of network traffic from the perspective of the global and local scaling exponents. It used this feature to analyze the fractal parameters of abnomal network traffic,trying to identify the relationship between changes of these parameters and the emergence of DDoS. Experimental results show that network traffic have the self-similar phenomena over large-scale and the multi-fractal phenomena over-small scale. It presented a method of DDoS attack detection based on Holder exponent.On the DARPA/Lincoln laboratory intrusion detection evaluation data set 2000,the experimental result shows that this method can detect the attack quickly and accurately.When the intermittent DDoS attack happen,this method is more effective than the traditional method.

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