论文部分内容阅读
The power-law node degree distributions of peer-to-peer overlay networks make them extremely robust torandom failures whereas highly vulnerable under intentional targeted attacks. To enhance attack survivability of these net-works, DeepCure, a novel heuristic immunization strategy, is proposed to conduct decentralized but targeted immunization.Different from existing strategies, DeepCure identifies immunization targets as not only the highly-connected nodes butalso the nodes with high availability and/or high link load, with the aim of injecting immunization information into justright targets to cure. To better trade off the cost and the efficiency, DeepCure deliberately select these targets from 2-1ocalneighborhood, as well as topologically-remote but semantically-close friends if needed. To remedy the weakness of existingstrategies in case of sudden epidemic outbreak, DeepCure is also coupled with a local-hub oriented rate throttling mechanismto enforce proactive rate control. Extensive simulation results show that DeepCure outperforms its competitors, producingan arresting increase of the network attack tolerance, at a lower price of eliminating viruses or malicious attacks.