计算机应用研究2018，Vol.35Issue(2)：582-585,4.DOI:10.3969/j.issn.1001-3695.2018.02.055
基于最优ABC-SVM算法的P2P流量识别
Identification of P2P traffic based on optimal ABC-SVM
摘要
Abstract
Currently peer-to-peer (P2P) network traffic identification is a hot topic in network management.Identification of P2P traffic based on support vector machine (SVM) is a commonly used P2P traffic identification method.However,the performance of SVM is mainly affected by the parameters and features used,the traditional method is to optimize the parameters and features of SVM separately.Hence,it is difficult to obtain the optimal SVM classifier on the whole.This paper proposed a P2P traffic identification approach based on artificial bee colony algorithm and the optimal SVM.Tuning parameters of SVM and feature selection was regarded as the optimization problem,which was handled with artificial bee colony algorithm synchronously.As a result,it obtained the optimal parameters and feature subset of SVM.The results show that the proposed method has good adaptability and classification accuracy on the real P2P data;it can simultaneously obtain the optimal feature subset and parameters of SVM and improve the overall performance.关键词
人工蜂群算法/支持向量机/特征选择/参数优化/P2P流量识别Key words
artificial bee colony algorithm/support vector machine/feature selection/parameter optimization/P2P traffic identification分类
信息技术与安全科学引用本文复制引用
王春枝,杜远丽,叶志伟..基于最优ABC-SVM算法的P2P流量识别[J].计算机应用研究,2018,35(2):582-585,4.基金项目
国家自然科学基金资助项目(61170135) （61170135）
