Application of Generalized Regression Neural Network in Cloud Security Intrusion Detection

Feng Gao
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引用次数: 2

Abstract

By using generalized regression neural network clustering analysis, effective clustering of five kinds of network intrusion behavior modes is carried out. First of all, intrusion data is divided into five categories by making use of fuzzy C means clustering algorithm. Then, the samples that are closet to the center of each class in the clustering results are taken as the clustering training samples of generalized neural network for the data training, and the results output by the training are the individual owned invasion category. The experimental results showed that the new algorithm has higher classification accuracy of network intrusion ways, which can provide more reliable data support for the prevention of the network intrusion.
广义回归神经网络在云安全入侵检测中的应用
采用广义回归神经网络聚类分析方法,对五种网络入侵行为模式进行了有效聚类。首先,利用模糊C均值聚类算法将入侵数据分为五类。然后,将聚类结果中离每一类中心最近的样本作为广义神经网络的聚类训练样本进行数据训练,训练输出的结果为个体拥有的入侵类别。实验结果表明,新算法对网络入侵方式具有较高的分类准确率,可以为网络入侵的防范提供更可靠的数据支持。
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