Abstract
With tremendous complex attacks on the network, network analysts not only need to understand but also predict the situation of network security. In the field of network security, the research on predicting network security situation has become a hot spot. The prediction of network security situation can dynamically reflect the security situation of the entire network and provide a reliable reference to ensure the network safety. This paper predicts the network security situation using the BP and the RBF neural networks, and then makes a comparison between the two methods. The results show that the effect of the model based on the BP neural network is better than that of the model based on the RBF neural network on predicting the network security situation.
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Zhang, Y., Jin, S., Cui, X., Yin, X., Pang, Y. (2013). Network Security Situation Prediction Based on BP and RBF Neural Network. In: Yuan, Y., Wu, X., Lu, Y. (eds) Trustworthy Computing and Services. ISCTCS 2012. Communications in Computer and Information Science, vol 320. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35795-4_83
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DOI: https://doi.org/10.1007/978-3-642-35795-4_83
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35794-7
Online ISBN: 978-3-642-35795-4
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