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Data stream classification method and system based on machine learning

A technology of machine learning and classification methods, applied in the field of computer networks, to achieve the effect of improving classification accuracy

Active Publication Date: 2019-07-19
ZHENGZHOU SEANET TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, from the perspective of improving the classification accuracy in the data, in order to further improve the classification accuracy, it is necessary to dig deep into the various information hidden in the data stream, and simply introducing new algorithm models is not enough

Method used

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  • Data stream classification method and system based on machine learning
  • Data stream classification method and system based on machine learning

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Embodiment Construction

[0027] The present invention will be further described now in conjunction with accompanying drawing.

[0028] refer to figure 1 , the present invention operates in a data stream classification system, the system includes a core module and an auxiliary module, the core module includes a data stream management and feature extraction module, a machine learning classification module, and a classification module; the auxiliary module includes a data stream capture Filter module, log encapsulation module.

[0029] The data flow capturing and filtering module is used to capture data packets on the network link, and this module will judge whether it is a legal data packet according to the packet header information of each data layer of the data packet and conforms to the input rules of the system, whether it is illegal or does not meet the requirements of the system. Packets for the rule will be dropped;

[0030] The data flow management and feature extraction module establishes a c...

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Abstract

The invention discloses a data stream classification method based on machine learning, which comprises the following steps: 1) capturing and filtering data streams on a network according to an input rule to obtain data packets meeting conditions; 2) establishing a data stream according to the quintuple information of the data packet, establishing an application stream in combination with the reverse data stream, extracting specified application stream feature information, and recording the application stream feature information in an application stream table; step 3) detecting whether the application flow completes an interaction process or not; if the application flow feature information is completed, packaging the application flow feature information into feature vectors, calling a machine learning classifier for classification to obtain a label La, entering a step 4), and otherwise, identifying the classification result of the application flow as an unknown application; and 4) searching an association information table to which the current application flow belongs, and determining a final classification result of the current application flow by combining machine learning classification information of historical application flows in the table. The method provided by the invention can effectively improve the classification accuracy of the current data flow.

Description

technical field [0001] The invention relates to the technical field of computer networks, in particular to a data flow classification method and system based on machine learning. Background technique [0002] Network data flow classification is an important part of network management work such as network security and service quality control. All data interacted with applications on the Internet is finally transmitted on the network in the form of data byte streams. By mapping network data streams with high-level applications, fine-grained regulation and review of traffic can be achieved. Traditional data flow classification methods are based on well-known ports and in-depth analysis based on packet load. With the increasing complexity of application types, well-known ports are no longer "famous", resulting in a decline in the accuracy of port-based classification methods; on the other hand, although methods based on deep packet inspection are more accurate, they have proble...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L12/26G06K9/62
CPCH04L43/026G06F18/24
Inventor 叶晓舟张润滋吴京洪
Owner ZHENGZHOU SEANET TECH CO LTD
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