Reputation systems represent soft security mechanisms that complement traditional information security mechanisms. They are now widely used in online e-commerce markets and communities in order to stimulate good behaviors as well as to restrain adverse behaviors. This paper analyzes the limitations of the conversational reputation models and proposes an incentive reputation model called the resilient reputation model (RRM) for the distributed reputation systems. The objective of this reputation model is not only to encourage the users to provide good services and, therefore, to maximize the probability of good transaction outcomes, but also to punish those adverse users who are trying to manipulate the application systems. The simulation results indicate that the proposed reputation model (RRM) could effectively resist against the common adverse behaviors, while protecting the profits of sincere users from being blemished by those adversaries.