A Sensitive and Robust Grid Reputation System Based on Rating of Recommenders

In this paper, we propose a sensitive and robust reputation system for service grid environments. A punishment factor is introduced to express the subjective opinion of evaluators and destroy the reputation of bad performers rapidly, which improves the sensitivity of the reputation system. By evaluating the reputation of recommenders, our solution filters out dishonest recommendations during the process of trust evaluation, thus making the reputation system more robust against vicious attacks launched by dishonest recommenders. Moreover, the introduction of inter-organizational trust enables the proposed reputation system to be more suitable for grid environments that span multiple autonomous organizations. Experimental results show that the proposed reputation system copes with changing behaviors of grid participants with high sensitivity and accuracy and works well even in extremely harsh environments full of dishonest recommenders.