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.