人工蜂群优化支持向量机算法在网络安全中的应用
发布时间：2018-10-18 14:09
【摘要】：针对支持向量机(SVM)性能的影响,探讨了人工蜂群算法(ABC)对SVM参数优化方法,建立了SVM参数优化模型,并将其用于网络安全中的网络入侵模型中.采用KDD 1999数据集进行仿真实验,验证了方法的有效性,结果表明,与遗传算法等传统优化算法相比,ABC优化的SVM有效地降低运行时间,可以获得更高的网络入侵检测率.
[Abstract]:In view of the effect of support vector machine (SVM) on the performance of (SVM), this paper discusses the optimization method of SVM parameters by artificial bee colony algorithm (ABC), establishes the SVM parameter optimization model, and applies it to the network intrusion model in network security. The effectiveness of the method is verified by using KDD 1999 dataset. The results show that compared with the traditional optimization algorithm such as genetic algorithm, the SVM optimized by ABC can effectively reduce the running time and obtain a higher network intrusion detection rate.
【作者单位】： 淮海工学院信息中心;
【分类号】：TP18;TP393.08
[Abstract]:In view of the effect of support vector machine (SVM) on the performance of (SVM), this paper discusses the optimization method of SVM parameters by artificial bee colony algorithm (ABC), establishes the SVM parameter optimization model, and applies it to the network intrusion model in network security. The effectiveness of the method is verified by using KDD 1999 dataset. The results show that compared with the traditional optimization algorithm such as genetic algorithm, the SVM optimized by ABC can effectively reduce the running time and obtain a higher network intrusion detection rate.
【作者单位】： 淮海工学院信息中心;
【分类号】：TP18;TP393.08
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