Abstract
In peer-to-peer (P2P) service-oriented environments, a peer may need to interact with unknown peers for the services or products provided. Thus the trust evaluation prior to and posterior to interactions becomes a very important issue, which may be based on other peers’ recommendations/evaluations. This chapter presents a dynamic peer trust evaluation model, which aims to measure responding peers’ recommendation trust, and hence filter out low credibility recommendations and obtain more accurate and objective trust values. In our model, prior to any interaction with an unknown peer (target peer), the mean trust value results from the evaluations (recommendations) given by responding peers. Posterior to interactions with the target peer, the trust values are aggregated from both responding peers’ recommendations and the requesting peer’s experience. On aggregating trust values, the weight to the requesting peer’s evaluation becomes bigger and bigger. Meanwhile, during this process, the credibility (recommendation trust) of each responding peer’s recommendation can be measured round by round. This helps filter out low credibility peers and improve the trust evaluation accuracy.
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