Modeling Internet-Scale Policies for Cleaning up Malware

Abstract

An emerging consensus among policy makers is that interventions undertaken by Internet Service Providers are the best way to counter the rising incidence of malware. However, assessing the suitability of countermeasures at this scale is hard. In this paper, we use an agent-based model, called ASIM, to investigate the impact of policy interventions at the Autonomous System level of the Internet. For instance, we find that coordinated intervention by the 0.2%-biggest ASes is more effective than uncoordinated efforts adopted by 30% of all ASes. Furthermore, countermeasures that block malicious transit traffic appear more effective than ones that block outgoing traffic. The model allows us to quantify and compare positive externalities created by different countermeasures. Our results give an initial indication of the types and levels of intervention that are most cost-effective at large scale.