An Adaptive Topology-Based Reputation Model for Unstructured P2P Networks

The reputation models based on distributed hash table are not suitable for unstructured P2P networks, whereas the existing reputation model for unstructured P2P networks requires a central server for assigning a set of trust management peers for any peer. We present a new reputation model for unstructured P2P networks in this paper. Differing from existing reputation models, in our model, each peer manages global reputation values of other peers in which it is interested. Local reputation values can be computed through feedback about transaction behaviors of peers, and aggregated to obtain global reputation values through the proposed reputation overlay network (RON). RON is comprised of similar interest peers, and can be evolved according to the proposed topology evolution protocol in this paper when forgery and collusion attacks occur. The theoretical analyses and experimental results show that, RON suppresses forgery and collusion attacks, has the desirable feature of reputation message costs, and this model satisfies demands of accurately computing global reputation values.