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Flat P2P communities have no authorities or supervisors to act as the root of trust, therefore trust is difficult to establish between stranger peers. A personalized P2P trust management framework is proposed in this paper, to help good peers build up trust between each other and avoid malicious peers. This framework differs from others in that it totally abandons the attempt to achieve a global view, but instead, evaluates trust from a subjective point of view and gives personalized decision support to each peer. With DHT-based backward query and collaborative-filtering-based evaluating, this new idea achieves three main advantages: free of central control, strong immunity to misleading recommendation, and limited traffic overload. We examine the performance of the proposed scheme and prove its effectiveness by a series of simulation experiments under different environmental configurations.