Flow Characteristic Selection Algorithm based on Dynamic Information in Deep Flow Inspection
In the technology of deep flow inspection, the recognition and classification of the data flow need using the flow characteristics. The currently characteristic selection algorithm based on the information measurement compute the information entropy of characteristics in the whole sample space, without considering the characteristic selection is a dynamic and changing process, also cannot accurately measure the dependence degree between characteristics in specific selection process. Therefore, this paper puts forward a characteristic selection algorithm based on dynamic information standard, this algorithm takes full account of the changes of information entropy in the characteristic selection process, by removing redundant and useless information, it would achieve the accurate and efficient selection of characteristics. The experimental data shows that, the classification performance of the proposed flow characteristic selection algorithm based on dynamic information is better than the other selection algorithm in the aspect of precision rate and recall rate.
DFI dynamic information characteristic selection
Guo Lei Wang Yadi Yao Qing Zhu Ke Yi Peng
Zhengzhou Information Science and Technology Institute Zhengzhou, China National Digital Switching System Engineering & Technological Research Center Zhengzhou, China
国际会议
哈尔滨
英文
1216-1219
2011-12-24（万方平台首次上网日期，不代表论文的发表时间）