人工蜂群优化支持向量机算法在网络安全中的应用
Application of Support Vector Machine Optimized by Artificial Bee Colony Algorithm in Network Security
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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: Parameters of support vector machine(SVM) is the key factor that impacts its performance.A parameter optimization method for SVM using artificial bee colony algorithm(ABC) is discussed and a parameter optimization model is established.The proposed algorithm's performance is tested by KDD 1999 data.The results show that the proposed algorithm decreased the running time efficiently and improved the accuracy of network intrusion detection.
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