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A Network Security Situation Prediction Method Based On SA-SSA

Under the influence of big data and artificial intelligence, Network security situation prediction has become a hot research field in recent years. Situation prediction is the premise of cyber security warning. The uncertainty and nonlinearity of situation data bring great challenges to the accuracy of situation prediction models. In order to improve the accuracy and performance of situation prediction model, Combined with Sparrow Search Algorithm and Simplicial Algorithm, this paper proposed a network security situation prediction method based on SA-SSA and utilized SA-SSA to optimize structural hyperparameters of neural network situation prediction model. The method based on SA-SSA has better performance than conventional situation prediction model, it improved the accuracy of neural network model and minimize the training loss. The proposed method was verified in Python. The results show that the method can accomplish the task of situation prediction with better capability.