Detecting malicious peers is a challenging task in peer-to-peer networks due to their decentralized structure and lack of central authority. Trust models can help identify malicious peers by maintaining information about peer relations and interactions. Keeping information about trust relations helps to reduce risks when providing or using services. This paper introduces two consistency concepts in trust management. Feedback consistency is used to evaluate how consistent feedback is with respect to past feedbacks. On the other side, peer consistency measures consistency of a peer's past feedbacks. These metrics help to reduce malicious interactions and increase successful downloads. Furthermore, the model offers better service quality for good peers by using consistency metrics. A file-sharing application is implemented on a simulation environment. The proposed model can effectively reduce the malicious download rate, even in 50% malicious environments, and increases successful download rates.