Network protection against worms and cascading failures using modularity paritioning

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Abstract

Communication networks are prone to virus and worms spreading and cascading failures. Recently, a number of social networking worms have spread over public Web sites. Another example is error propagation in routing tables, such as in BGP tables. The immunization and error curing applied to these scenarios are not fast enough. There have been studies on the effect of isolating and curing network elements, however, the proposed strategies are limited to node removals. This paper proposes a link isolation strategy based on the quarantining of susceptible clusters in the network. This strategy aims to maximize the epidemic control while minimizing the impact on the clusters performance. We empirically study the influence of clustering on robustness against epidemics in several real-world and artificial networks. Our results show an average curing rate improvement above 50% for the studied real-world networks under analysis.