PHAT: A Preference and Honesty Aware Trust Model for Web Services

Trust is one of the most critical factors for a service requestor when selecting a service from a large pool of candidate services. However, existing web service trust models either do not consider users' preferences for different quality of service (QoS) attributes, or ignore the impact of vicious ratings on trust evaluation. To address these gaps, PHAT, a dynamic trust evaluation model with dual consideration of users' preferences and false ratings, is proposed in this paper. The model introduces an approach to automatically mine users' preferences from their requirements. The preferences are then used to determine the weight of each QoS attribute when integrating trust into multi-dimensional QoS attributes. The “local” trust on a service is derived by combining the trust on QoS attributes and the user's subjective ratings. Then, the users are divided into different groups according to their QoS preferences, and the honesty of each group is assessed by filtering out dishonest users based on a hybrid approach combining rating consistency clustering with an average method. Finally, the weight on ratings is dynamically adjusted according to the results of honesty assessment when calculating the global trustworthiness, namely, the reputation of a service. The proposed model is evaluated with real-world QoS data, and the results indicate that PHAT works well on personalized evaluation of trust, and can effectively dilute the influence of malicious ratings.