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Modeling Internet-Scale Policies for Cleaning up Malware

机译:为清理恶意软件建模Internet规模策略

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摘要

An emerging consensus among policy makers is that interventions undertaken byInternet Service Providers are the best way to counter the rising incidence ofmalware. However, assessing the suitability of countermeasures at this scale ishard. In this paper, we use an agent-based model, called ASIM, to investigatethe impact of policy interventions at the Autonomous System level of theInternet. For instance, we find that coordinated intervention by the0.2%-biggest ASes is more effective than uncoordinated efforts adopted by 30%of all ASes. Furthermore, countermeasures that block malicious transit trafficappear more effective than ones that block outgoing traffic. The model allowsus to quantify and compare positive externalities created by differentcountermeasures. Our results give an initial indication of the types and levelsof intervention that are most cost-effective at large scale.
机译:决策者之间逐渐形成的共识是,互联网服务提供商采取的干预措施是应对恶意软件不断上升的最好方法。但是,很难评估这种规模的对策的适用性。在本文中,我们使用称为ASIM的基于代理的模型来研究策略干预对Internet自治系统级别的影响。例如,我们发现0.2%最大的AS的协调干预比所有AS中30%的不协调努力更有效。此外,阻止恶意传输流量的对策似乎比阻止传出流量的对策更有效。该模型允许我们量化和比较由不同对策产生的正外部性。我们的研究结果初步表明了大规模干预最具成本效益的干预类型和水平。

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