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Trust and reputation model in peer-to-peer networks

机译:对等网络中的信任和信誉模型

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摘要

It is important to enable peers to represent and update their trust in other peers in open networks for sharing files, and especially services. We propose a Bayesian network-based trust model and a method for building reputation based on recommendations in peer-to-peer networks. Since trust is multifaceted, peers need to develop differentiated trust in different aspects of other peers' capability. The peer's needs are different in different situations. Depending on the situation, a peer may need to consider its trust in a specific aspect of another peer's capability or in multiple aspects. Bayesian networks provide a flexible method to present differentiated trust and combine different aspects of trust. The evaluation of the model using a simulation shows that the system where peers communicate their experiences (recommendations) outperforms the system where peers do not share recommendations with each other and that a differentiated trust adds to the performance in terms of percentage of successful interactions.
机译:使对等体能够代表并更新其对开放网络中其他对等体的信任以共享文件(尤其是服务)非常重要。我们提出了一种基于贝叶斯网络的信任模型,以及一种基于对等网络中的建议建立信誉的方法。由于信任是多方面的,所以对等方需要在其他对等方能力的不同方面发展差异化的信任。在不同情况下,对等方的需求是不同的。根据情况,对等方可能需要在另一个对等方能力的特定方面或多个方面考虑其信任。贝叶斯网络提供了一种灵活的方法来呈现差异化的信任并组合信任的不同方面。使用仿真对模型进行的评估表明,对等方交流其经验(建议)的系统优于对等方彼此不共享建议的系统,并且在成功互动的百分比方面,差异化的信任增加了性能。

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