Network data flow classification method and system
Abstract:
A network data flow classification method related to artificial intelligence includes collecting an information set, including a plurality of pieces of dimension information, of a to-be-processed data flow, establishing a static behavior model and a dynamic behavior model of each piece of dimension information in the information set, where the static behavior model represents a value selection rule of the dimension information, and the dynamic behavior model represents a correlation relationship of the dimension information between two adjacent time moments, obtaining, using the static behavior model and the dynamic behavior model respectively, a static model distance and a dynamic model distance between the to-be-processed data flow and a data flow of each target application type, determining an application type of the to-be-processed data flow based on the static model distance and the dynamic model distance.
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