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

Abstract:

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.

• Periodical: Applied Mechanics and Materials (Volumes 519-520)
• Pages: 262-270
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.519-520.262
• Online since: February 2014
• Authors: Zhuo Yi*, Shi Jun Yao, Liang Wang
• Keywords: Biological Invasions, Brittle Point and Brittle seam, Brittle Seam Mining, Cloud Computing, DDoS Attacks Detection, Situation Assessment andPrediction

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