Abstract
Aiming at the threat of power information network attack, a situation awareness method of LDA-RBF is proposed and applied to power information network security. Firstly, the linear discriminant analysis (LDA) is used to optimize the sample data of power information network, and the feature indexes are effectively fused and extracted to obtain the best projection, so that the samples have the best separability; Then the preprocessed data is used as the training data of RBF neural network to realize the security situation awareness of power information network and identify the intrusion attacks existing in power information network. In this paper, the KDDCup99 dataset and the network attack data under the electric power information network environment are used to simulate the method proposed in this paper. The comparison results verify that the network security situation awareness method based on LDA-RBF proposed in this paper can achieve more accurate and efficient network security situation awareness.
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