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A New Detection Approach Based on the Maximum Entropy Model

机译:基于最大熵模型的新检测方法

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摘要

The maximum entropy model was introduced and a new intrusion detection approach based on the maximum entropy model was proposed. The vector space model was adopted for data presentation. The minimal entropy partitioning method was utilized for attribute discretization. Experiments on the KDD CUP 1999 standard data set were designed and the experimental results were shown. The receiver operating characteristic(ROC) curve analysis approach was utilized to analyze the experimental results. The analysisresults show that the proposed approach is comparable to those based on support vector machine (SVM) and outperforms those based on C4. 5 and Naive Bayes classifiers. According to the overall evaluation result, the proposed approach is a little better than those based on SVM.
机译:介绍了最大熵模型,提出了一种基于最大熵模型的入侵检测新方法。向量空间模型用于数据表示。最小熵划分方法用于属性离散化。设计了KDD CUP 1999标准数据集上的实验,并显示了实验结果。利用接收器工作特性曲线分析方法对实验结果进行分析。分析结果表明,该方法可与基于支持向量机(SVM)的方法相媲美,并且优于基于C4的方法。 5和朴素贝叶斯分类器。根据总体评估结果,所提出的方法比基于SVM的方法要好一些。

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