Performance Analysis of Large Scale Peer-to-Peer Overlays using Markov Chains

In this paper we consider the problem of targeted attacks in large scale peer-to-peer overlays. Targeted attacks aimed at exhausting key resources of targeted hosts to diminish the target node capacity to provide or receive services. To defend the system against such attacks, we rely on clustering and implement induced churn to preserve randomness of nodes identiers so that adversarial predictions are impossible. We propose robust join, leave, merge and split operations to discourage brute force denial of services and pollution attacks. We show that combining a small amount of randomization in the operations, and adequately tuning the sojourn time of peers in the same region of the overlay allows to decrease the eect of targeted attacks at cluster level, but more importantly to prevent pollution propagation in the whole overlay