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Research on application of Bayesian discriminant method in intrusion detection model

机译:贝叶斯判别方法在入侵检测模型中的应用研究

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摘要

An intrusion detection model based on bayesian discriminant method is constructed in this paper. The intrusion detection problem is transformed into a discriminant classify problem in the model. We use stepwise discriminant method in selecting significant discriminatory variables to decrease computational complexity. The model is trained and validated by using the denial of service (DoS) attack data of KDD CUP99's data set. The result of the experiment shows high correctly identified percentage of the model. Intrusion detection system can be constructed with the model when there are sufficient network packet records as a support.
机译:建立了基于贝叶斯判别方法的入侵检测模型。入侵检测问题在模型中转化为判别分类问题。我们使用逐步判别法来选择重要的判别变量以降低计算复杂度。该模型通过使用KDD CUP99数据集的拒绝服务(DoS)攻击数据进行训练和验证。实验结果表明正确识别出的模型百分比很高。当有足够的网络数据包记录作为支持时,可以使用该模型构建入侵检测系统。

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