SELECTING TRUSTWORTHY CLIENTS IN THE CLOUD

With the recent increase demand for cloud services, handling clients' needs is getting increasingly challenging. Responding to all requesting clients with no exception could lead to security breaches, and since it is the provider's responsibility to secure not only the offered cloud services but also the data, it is important to ensure clients reliability. Although filtering clients in the cloud is not so common, it is required to assure cloud safety. In this paper, we made use of multi agent system interaction mechanisms to handle the cloud interactions for the providers' side, and of Particle Swarm Optimization to select the and determine the accurate trust weight and therefore to filtrate the clients by determining malicious and untrustworthy clients. The selection depends on previous knowledge and overall rating of trusted peers. The conducted experiments proves that the combination between MAS, PSO and trust outputs relevant results with different number of peers, the solution is able to converge to the best result after small number of iterations. To explore more space and scenarios, synthetic data was generated to improve the model's precision .