Collusive User Removal and Trusted Composite Web Service Selection based on QoS attributes

Generally web service selection is performed based on nonfunctional (Quality of Service) attributes. But Quality of Service (QoS) attribute values may not be equal to the published values by the service providers. Therefore, the users want to concern about the trustworthiness of the services or service providers. The trustworthiness of a service is measured by the users' ratings. There may be the dishonest users who provide the fake ratings for commercial benefit. These users are called malicious or collusive users and can be treated like outliers. Now, we have proposed an approach to identify these outliers using data mining approach. Then Composite Web Service Selection is performed using Genetic Algorithms (GA). The problem is to find an optimal concrete service composition plan under users' QoS constraints. The QoS-aware composite web service selection is NP-hard problem. But it can be mapped with Multi-dimensional Multi-choice Knapsack Problem(MMKP), which is NP-complete[6]. Therefore, we use Genetic Algorithm(GA) to find the near-optimal composite service plan with QoS constraints.