In order to depict high dynamic of entity behavior quickly and accurately,a trust evaluation model based on continuous-time hidden Markov process was proposed. Different from the trust models on discrete-time hidden Markov chain,this model fully considered time dependence of trust,combined time intervals between the interactions and made the trust evaluation problem boil down to the learning problem of continuous-time hidden Markov process. Then an algorithm for solving the optimal parameters of hidden Markov process was given with the improved harmony algorithm,which could effectively guarantee the global search space and achieve a better solution.On this basis,the trust degree could be predicted using the existing interaction sequences and optimal parameters.Simulation results showed that the model is able to quickly reflect the dynamic of entity behavior,has high accuracy and resists the malicious attacks.
