首页> 外文会议>Computational Intelligence and Security, 2009. CIS '09 >Predators Combat Good Point Set Scanning-Based Self-Learning Worms
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Predators Combat Good Point Set Scanning-Based Self-Learning Worms

机译:捕食者与善点集扫描自学习蠕虫作斗争

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Good point set scanning-based self-learning worms can reach a stupendous propagation speed in virtue of the non-uniform vulnerable-host distribution than that of traditional worms. In order to combat self-learning worms, this paper proposes an interaction model. Using the interaction model, we obtain the basic reproduction number. The impact of different parameters of predators is studied. Simulation results show that the performance of our proposed models is effective in combating such worms, in terms of decreasing the prey infectives and reducing the prey propagation speed.
机译:与传统蠕虫相比,基于点集扫描的自学习蠕虫由于其脆弱的宿主分布不均匀,因此可以达到惊人的传播速度。为了对抗自学习蠕虫,本文提出了一种交互模型。使用交互模型,我们获得基本的再现数。研究了捕食者不同参数的影响。仿真结果表明,在减少猎物感染和降低猎物传播速度方面,我们提出的模型在对抗此类蠕虫方面是有效的。

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