Dynamic Service Selection with Reputation Management

In open and dynamic environments, reputation-based trust is a key issue for service selection which is based on the prediction of services´ performance. Typically, the trust and reputation evaluation is based on the feedback of the service quality from all service users. The crucial issue in this evaluation is to detect and deal with false or unfair feedback from dishonest providers and cheating users. In this paper, we first present a dynamic service selection framework then introduce a semantic match and rank algorithm to enable the automatic selection. Furthermore, we propose a reputation assessment approach to address trust and reputation of service and service user in various realistic cheating behaviors. Finally, to the best of our knowledge, a set of empirical studies have been conducted to demonstrate that our solution gains good results under collaboration attacks of various cheating behaviors.