| 改进的支持向量机无线网络安全检测算法模型 |
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| 引用本文： | 黄小龙.改进的支持向量机无线网络安全检测算法模型[J].科技通报,2012,28(2):49-51. |
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| 作者姓名： | 黄小龙 |
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| 作者单位： | 百色学院数学与计算机信息工程系,广西百色,533000 |
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| 基金项目： | 广西教育厅科研项目(201010LX498);广州大学——百色学院合作科学研究项目(GBK2010010) |
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| 摘 要： | 针对传统网络入侵算法在WLAN中的异常检测效率低,提出了一种SVM算法的WLAN入侵检测方法,首先对网络入侵的数据计算信息增益,从原始数据中选取对分类结果影响较大的特征属性,对SVM参数进行优化,最后采用优化的SVM算法对无线网络数据进行检测,得出网络入侵结果.实验结果表明,提出的算法检测正确率高、漏报率与误报率低,具有很好的应用前景.
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| 关 键 词： | 支持向量机 WLAN 信息增益 入侵检测 |
Improved Support Vector Machine Wireless Network Security Detection Algorithm Model |
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| HUANG Xiaolong.Improved Support Vector Machine Wireless Network Security Detection Algorithm Model[J].Bulletin of Science and Technology,2012,28(2):49-51. |
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| Authors: | HUANG Xiaolong |
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| Institution: | HUANG Xiaolong (Department of Mathematics & Computer Information Engineering,Baise University,Baise 533000,China) |
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| Abstract: | This paper proposed a support vector machine SVM algorithm for WLAN intrusion detection,first calculates the information gain of network intrusion data,and selects the characteristics of properties having a greater impact on the classification from the raw data to optimize the parameters of SVM,Finally,an optimized SVM algorithm is used to detect the wireless network data to obtain the behavior of network detection.Simulation results show that model of SVM-based WLAN intrusion detection has a high correct detecting rate,a low negative rate and wrong alarm rate. |
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| Keywords: | SVM WLAN information gain Intrusion detection |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
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