Fast quarantining of proactive worms in unstructured P2P networks
Journal of Network and Computer Applications
Modeling and Defending against Adaptive BitTorrent Worms in Peer-to-Peer Networks
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
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Internet worms pose a serious and ongoing threat to system security, often resulting in significant service downtime and disruption. In recent years peer-to-peer (p2p) networks have become a target for the deployment of worms as their high connectivity allows for rapid dissemination and homogeneity of the adopted software platform ensures the existence of common susceptibilities. In this paper we observe that peer similarity in p2p networks can greatly increase overall vulnerability; peers with largely different system characteristics are unlikely to be infected by the same worm. With this in mind we present dijest — an autonomic method for neighbour selection based on heterogeneity. Our results show the efficacy of di-jest in reducing the spread rate and potency of p2p worms. By selecting neighbours with different system characteristics dijest can reduce the number of peers infected by a worm by up to 80%.