Online encrypted traffic classification method based on CNN and LSTM
A traffic classification and sub-flow technology, applied in the field of computer networks, can solve problems such as data imbalance, difficulty in obtaining ideal data sets, and increased complexity of feature matching, so as to achieve the effect of improving reliability and accuracy
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[0021] The following describes the technical solutions in the embodiments of the present invention clearly and completely with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.
[0022] Traditional traffic identification methods have great limitations in the identification of encrypted traffic due to the dynamic nature of ports, the difficulty of extracting and matching payload expressions and matching, and the high consumption of time and space resources for behavioral feature analysis. However, based on various machine learning methods, Usually, only various statistical characteristics of network data streams are consi...
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