Affiliations: College of Computer Science, Jiangxi University of Engineering, Xinyu 338000, Jiangxi, China
Correspondence:
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Corresponding author: Zhicheng Wen, College of Computer Science, Jiangxi University of Engineering, Xinyu 338000, Jiangxi, China. Tel.: +86 15873372746; E-mail: [email protected].
Note: [1] Liang Shen (1978-), male, Hukou county, Jiangxi Province, Han, master’s degree, associate professor, majoring in: network security, trusted software. Corresponding author: Zhicheng Wen (1972-), male, Dong’an county, Hunan province, Han, Ph.D., professor, majoring in: network security, trusted software.
Abstract: Existing network security prediction methods for the cloud environment are limited in terms of both accuracy and real-time performance. In this paper, we address these issues with a proposal for a method based on grey neural network to predict network security situations in cloud environments. First, we explore security factors for network security situation awareness based on classification and fusion techniques in order to generate awareness indexes. Through this, we establish a hierarchical index system for network security situation. Then, a method is elaborated that combines grey theory and neural networks to predict network security situations by analyzing the features of grey and neural networks that combine high accuracy and real-time performance. Finally, through experiments with simulated data, a network prediction algorithm for security situations is verified. Results of experiments show that the method is both correct and feasible.
