A statistical user-behavior trust evaluation algorithm based on cloud model

User behavior is the trace or proof of the user´s impact on the environment when he tries to acquire some information or complete a job in a particular environment. Cross-sectional study of user behavior focuses on the deviation between the individual behavior and the group behavior. From this perspective, we propose a statistical user-behavior trust evaluation algorithm based on cloud model for statistics-based behaviors which generates the threshold for each type of behaviors and each user´s membership degree between the user´s performance and the calculated threshold. And then the membership degree and the behavior weight will be together sent to calculate the user´s behavior trust evaluation value using a simple normalized method. Finally, as the basis of intra-domain trust and recommendation trust, behavior trust could help for users´ further dynamic authorization of access control.