A Comparative Study on Reputation Management in Social Cloud: Validating Our Proposed Trust Architecture with Multiple Datasets

This paper presents a comparative study on reputation management in social cloud, focusing on validating a novel trust-based architecture through experimentation with multiple real-world datasets. The proposed architecture incorporates various components such as feedback collection, trust computation, and reputation propagation, aiming to improve reliability and robustness in managing user reputations within social clouds. We compare our approach with existing state-of-the-art methods and evaluate its effectiveness by analyzing results from four large-scale public datasets. Through extensive experiments, we demonstrate that our proposed architecture outperforms traditional approaches in terms of accuracy, efficiency, and adaptability. Additionally, we discuss insights gained from this research and outline future directions for improving trust and reputation management in social clouds.