| 摘要 |
A traffic data classification method and device. The method comprises: collecting data packets, regrouping the data packets into a flow to generate traffic data, and according to service type marking which is conducted on some traffic data in the traffic data in advance, for each service category, forming a learning sample correspondingly, and setting the rest in the traffic data as a traffic data set to be classified; extracting a common numerical attribute feature set of each piece of traffic data in the traffic data set, and organizing the traffic data in the traffic data set into a flow record which is composed of the common numerical attribute feature set; and according to the learning sample, calculating a common numerical attribute feature set of each service category in the flow record by means of subspace clustering, and according to the common numerical attribute feature set of each service category which is obtained by calculation and the common numerical attribute feature sets of the traffic data in the flow record, conducting service type marking on the traffic data in the traffic data set. A new traffic service feature in a network is updated in time. |
