欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
讨论了基于粗糙集特征约简的SVM（支持向量机）异常检测方法,对源自KDD99的实验数据集分别采用SVM和特征约减后SVM进行仿真实验,依据实验结果的比较,说明在网络异常检测中基于特征约减后的SVM和直接采用SVM相比,在保持检测精度不显著降低的同时,前者能够有效的缩短训练时间.
英文摘要：
Discussed method of network anomaly detectio n using rough-set-attribution-reduction-based SVM.The testing data set from KDD 99 were experimented by respectively using attribution-reduction-based SVM and original SVM.The experiment results showed that,compared with applying SVM directly,to apply attribution-reduction-based SVM in network anomaly detection can reduce effectively training time without obviously losing detection accuracy.
同期刊论文项目
同项目期刊论文
期刊信息
位置：