A prediction model of cloud security situation based on evolutionary functional network

Aiming at the dynamic uncertainty and prediction accuracy of security situation prediction in complex cloud network environment, a prediction model of cloud security situation based on evolutionary functional network is proposed. Firstly, the evolutionary functional network model is constructed by combining the evolutionary algorithm with the functional network, which solves the problem of basis function selection and basis function coefficient correction of the prediction model. Secondly, the stochastic approximation algorithm is used to process and comprehend the cloud security situation elements, and the computational complexity of the prediction model is reduced by the dimensionality reduction method. Finally, by constructing the credibility matrix of the uncertain influence relationship of security situation elements, we use the multivariate non-linear regression algorithm to predict the cloud security situation. The simulation results show that compared with BP model and RAN-RBF model, the prediction accuracy of the proposed model is improved by 8.2% and 6.9% respectively, and the convergence efficiency is improved by 12.3% and 10.8% respectively.