A Similar Recommendation Selection-Based Trust Model In Grid

Along with emergence of grid technology, the user management isn't central, closed and controllable. Grid system is facing all kinds of threats that include threats from the inner of system and threats from the outer of system. Traditional computer security mainly researches on preventing intrusion from the outer of system. However, traditional method has nothing to do with threads from the inner of system. So, it is necessary to evaluate the network behavior of users in grid computing. Thus, evaluation of the user's behavior can reflect his reliability. This dissertation studies how to build trust model for grid computing in order to find out malicious users and improve security and reliability of system.This dissertation analyses trust models available in Grid system and has found that there are some shortcomings in these trust models. First of all, when there are some malicious nodes in Grid, those trust models can not evaluate trust degree accurately, because of the bad-mouthing of these malicious nodes. Secondly, there may be some collusion in Grid system. When the scale of collusion become large, it will be hard for these trust models to make right evaluation. To solve these problems, this paper proposed a similar recommendation selection based- trust model in Grid. New trust model will improve the evaluation of trust degree and make trust degree more accurate by selecting similar recommendation.At last, this paper designed a series of simulation such as validating the characteristic of new model, control to malicious nodes, infection to the model with dishonest nodes of different percents. These experiments validated the sensitivity, astringency, validity and rationality with behavior in the two-layer trust model based on behavior.