Researches on Brittle Seam Mining based Situation Assessment and Prediction Mechanism of DDoS Attacks in Cloud Computing Platform

被引:0
|
作者
Zhuo, Yi [1 ]
Yao, Shijun [1 ]
Liang, Wang [1 ]
机构
[1] Informat Engn Univ, Sch Sci, Zhengzhou 450001, Peoples R China
来源
关键词
Biological Invasions; Brittle Point and Brittle seam; Brittle Seam Mining; Situation Assessment and Prediction; Cloud Computing; DDoS Attacks Detection;
D O I
10.4028/www.scientific.net/AMM.519-520.262
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
According to the problem of Situation Assessment and Prediction of DDoS Attacks in Cloud Computing Platform, the concepts of Brittle Point and Brittle seam were introduced to describe the situation of an eco-system according to ranked node availability, and a Situation Assessment and Prediction Mechanism based on the Brittle Seam Mining Algorithm was proposed. In the Brittle Seam Mining Algorithm, biological features of DDoS attacks and cloud computing platform were analyzed from the point of bio-dynamics, and the analysis results indicate that bandwidth loads of the normal user access from different populations wound not reach the brittle point of an eco-system, while bandwidth load of victim under DDOS attacks will reach the brittle point. The Biological Invasions Model such as the population diffusion reaction model and the population reproduction model are adopted to predict and detect the Brittle Point and Brittle seam. Meanwhile, the GIS technology was used in the visualization of Brittle seam. The simulation results verify the applicability of this method.
引用
收藏
页码:262 / 270
页数:9
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