Evaluating Trust Management in Social Networks Using Eviden Theory

Various methods have been presented to evaluate trust management between users in social networks. Individual and subjective diagnosis is less considered in the evaluation of trust and often a general and general model is presented for all users. trust evaluation without considering the personal and mental characteristics of users is not effective. in the proposed method of this research, users' characteristics are calculated and their importance is determined using fuzzy rough set theory. users' characteristics are combined and aggregated by considering their importance and using Dempster Shafer theory of evidence. the sets of trust and distrust values and ambiguity are evaluated to determine the degree of trust. the final values are used to make a trust decision and create a secure connection. the level of user trust in the entire network is determined by all users. the comprehensive performance of the proposed method and RTARS, ABC, DSL-STM and AUTOMATA algorithms have been compared in four evaluation indices and in 10 independent implementations. the obtained results show the improvement of the trust decision and the creation of safe communication in social networks. the proposed algorithm has been able to correctly decide the trust of users in social networks with 92.54% accuracy. the experimental results show that the proposed method is able to infer trust more accurately than the previous methods.