改进的支持向量机无线网络安全检测算法模型

Improved Support Vector Machine Wireless Network Security Detection Algorithm Model

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。

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.