云计算环境下蠕虫监控检测与传播模型的研究

针对云计算环境下蠕虫病毒的监控检测及其传播模型的研究,提出了一种云计算环境的蠕虫传播模型——CWPM(Cloud Worm Propagation Model),采用微分方程方法建立了CWPM的数学模型,通过实验定性分析了影响CWPM模型的因素,并与已有传播模型作比较,验证了CWPM传播模型的合理性和有效性。基于GMA模型提出了云计算环境下蠕虫监控检测框架——CWMDF(Cloud Worm Monitor and Detection Framework)。利用CWPM模型对CWMDF的合理性进行了理论分析,提出了系统敏感度参数,通过实验分析CWMDF下影响系统敏感度参数的因素,根据实验结果给出了CWMDF实现的改进方案和建议以达到理想预警效果。实验证明,CWMDF框架的部署能够有效地降低云中蠕虫传播速度,降低蠕虫爆发峰值以及延迟峰值出现的时间。

Research of Worm Monitoring Detection and Propagation Models Under Cloud Computing Environment

Aiming at the studying of test and propagation model of the internet worm under cloud computing environment. Qualitative analysis of factors affecting CWPM and comparison with existing propagation model verify the rationality and effectiveness of the CWPM by a series of simulations. Based on GMA, CWMDF(Cloud Worm Monitor and Detection Framework) is proposed to further validate the CWPM. The rationality of CWMDF is proved by analyzing with CWPM. Recommendations witch implement the CWMDF was gave according to the experimental results, qualitative analysis of the factors that affect system sensitivity to achieve the desired result of worm warning. The experiment results prove the deployment of CWMDF can effectively reduce the worm propagation speed and outbreak peak, delay the arrival of outbreak peak.