| A New Detection Approach Based on the Maximum Entropy Model |
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| 作者姓名： | DONG Xiaomei XIANG Guang YU Ge LI Xiaohua |
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| 作者单位： | School of Information Science and Engineering, Northeastern University, Shenyang 110004, Liaoning, China |
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| 基金项目： | 教育部高等学校博士学科点专项科研基金;教育部优秀青年教师资助计划 |
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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 diseretization. Experiments on the KDD CUP 1999 standard data set were designed and the experimental results were shown. The receiver operating eharaeteristie（ROC） curve analysis approach was utilized to analyze the experimental results. The analysis results show that the proposed approach is comparable to those based on support vector maehine（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.
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| 关 键 词： | 侵入检测 网络安全 最大熵模型 SVM 接收器操作特征曲线 |
| 文章编号： | 1007-1202（2006）06-1765-04 |
| 收稿时间： | 2006-05-30 |
A new detection approach based on the maximum entropy model |
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| DONG Xiaomei XIANG Guang YU Ge LI Xiaohua.A New Detection Approach Based on the Maximum Entropy Model[J].Wuhan University Journal of Natural Sciences,2006,11(6):1765-1768. |
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| Authors: | Dong Xiaomei Xiang Guang Yu Ge Li Xiaohua |
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| Institution: | (1) School of Information Science and Engineering, Northeastern University, 110004 Shenyang, Liaoning, China |
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| Abstract: | 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 analysis results 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. |
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| Keywords: | intrusion detection maximum entropy model classifier support vector machine receiver operating characteristic curve |
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