首页> 外文期刊>Journal of Theoretical and Applied Information Technology >INTRUSION DETECTION SYSTEM USING BOOTSTRAP RESAMPLING APPROACH OF T2 CONTROL CHART BASED ON SUCCESSIVE DIFFERENCE COVARIANCE MATRIX
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INTRUSION DETECTION SYSTEM USING BOOTSTRAP RESAMPLING APPROACH OF T2 CONTROL CHART BASED ON SUCCESSIVE DIFFERENCE COVARIANCE MATRIX

机译:基于连续差分协方差矩阵的T2控制图自举重采样法的入侵检测系统

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The multivariate control chart is one of SPC method that is often used in intrusion detection. The Hotelling?s T2 control chart with Successive Difference Covariance Matrix (SDCM) is the robust method that can detect outliers in the process data for individual observation. This method will effective to be applied in Intrusion Detection System (IDS) because it can detect the anomaly or outliers in the network. The problem arise when the exact distribution of this method has not determined. Bootstrap is one of the nonparametric method that widely used to estimate the parameter without any distribution assumption applied to overcome the problem. In this research, the Hotelling?s T2 control chart is improved using the SDCM while its control limits is calculated using bootstrap resampling method. The proposed method is applied in IDS and its performance is compared to the other control chart approaches. The performance evaluation result shows that the proposed IDS with bootstrap control limit performs better than the other control chart approaches for testing dataset. Moreover, the proposed IDS outperforms the other classification methods.
机译:多元控制图是入侵检测中经常使用的SPC方法之一。具有连续差分协方差矩阵(SDCM)的Hotelling的T2控制图是一种鲁棒的方法,可以检测过程数据中的异常值以进行单独观察。此方法将有效地应用于入侵检测系统(IDS),因为它可以检测网络中的异常或异常值。如果尚未确定此方法的确切分布,则会出现问题。 Bootstrap是一种非参数方法,广泛用于估算参数,而无需采用任何分布假设来克服该问题。在这项研究中,Hotelling的T2控制图使用SDCM进行了改进,而其控制范围则使用自举重采样方法进行了计算。将该方法应用于IDS,并将其性能与其他控制图方法进行了比较。性能评估结果表明,所提出的具有自举控制极限的IDS的性能优于其他控制图方法来测试数据集。此外,提出的IDS优于其他分类方法。

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