PURGING OF UNTRUSTWORTHY RECOMMENDATIONS FROM A GRID

In grid computing, trust has massive significance. There is lot of research to propose various models inproviding trusted resource sharing mechanisms. The trust is a belief or perception that variousresearchers have tried to correlate with some computational model. Trust on any entity can be direct orindirect. Direct trust is the impact of either first impression over the entity or acquired during some directinteraction. Indirect trust is the trust may be due to either reputation gained or recommendations receivedfrom various recommenders of a particular domain in a grid or any other domain outside that grid oroutside that grid itself. Unfortunately, malicious indirect trust leads to the misuse of valuable resources ofthe grid. This paper proposes the mechanism of identifying and purging the untrustworthyrecommendations in the grid environment. Through the obtained results, we show the way of purging ofuntrustworthy entities.