Method and device for classifying network traffic data

A technology of flow data and network flow, applied in data exchange network, digital transmission system, instrument, etc., can solve the problem of not being able to classify all flow data

Active Publication Date: 2017-03-08
ZTE CORP
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The invention provides a method and device for classifying network traffic data, which solves the problem that all traffic data cannot be classified equally in the prior art

Method used

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  • Method and device for classifying network traffic data
  • Method and device for classifying network traffic data
  • Method and device for classifying network traffic data

Examples

Experimental program
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Embodiment 1

[0088] See figure 1 As shown, the classification method of network traffic data provided in this embodiment includes:

[0089] S101: Obtain N traffic data samples from the network data stream, and obtain the data volume of each traffic data sample and the identification of each traffic data sample; the data volume of each traffic data sample is the traffic data itself The storage space occupied; the identification of each flow data sample is the identification that the flow data is different from other flow data, and may include: the preset identification bit of the flow data or the flow data itself; specifically, when obtaining Before the traffic data sample, it also includes preprocessing the traffic data in the network data stream, including: filtering data and limiting the rate of the message; by limiting the rate of the data message, the load of the system processing is reduced, and at the same time, with the help of access control Technology to filter illegal messages a...

Embodiment 2

[0172]This embodiment provides a device for classifying network traffic data. The classifying device includes: a data acquisition module, configured to acquire N traffic data samples from network data streams, and acquire the data size and the size of each traffic data sample. The identification of flow data samples; the first classification module is used to divide the N data flow samples into K categories according to the data volume of each flow data sample; Mark each flow data in each category to be sampled multiple times to obtain the number of times of successful sampling and the number of times of sampling failure. The number of times of sampling of flow data in the same category is the same; the parameter calculation module is used to The number of times and the number of sampling failures obtain the expectation and uncertainty probability of each flow data in its corresponding class; the weight module is used to calculate the weight of each flow data in its class accor...

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Abstract

The invention discloses a method and device for classifying network traffic data. N flow data samples are obtained from network data stream, and the data size of each flow data and the identification of each flow data are obtained. According to the data size of each flow data, N flow data are divided into K categories. According to the identification of each flow data, the multiple times of sampling of each flow data in each category are carried out, the number of times of successful sampling and the number of times of failed sampling are obtained, and the numbers of times of sampling of the flow data in a same category are the same. According to the number of times of successful sampling and the number of times of failed sampling, the expectation and uncertainty probabilities of each flow data in a corresponding category are obtained. The weight of the category where each flow data is located is calculated according to the expectation and uncertainty probabilities. According to the weight of the category where each flow data is located, the flow data is reclassified according to a preset classification rule. The problem that the all flow data cannot be randomly classified in the prior art is solved.

Description

technical field [0001] The invention relates to the field of data management of data communication, in particular to a method and device for classifying network flow data. Background technique [0002] Currently, network traffic classification methods adopted in the prior art mainly include methods based on port number mapping, payload analysis, and machine learning. For example, in traffic classification based on port number mapping, with the continuous development of Internet technology, many emerging network services (such as P2P, online games, etc.) use dynamically negotiated port numbers for communication, making the method based on port number mapping impossible To ensure completely accurate network traffic analysis and statistics, the method is therefore subject to many limitations. The main manifestations are: 1) port numbers and applications are not always associated, IANA (The Internet Assigned Numbers Authority, Internet Number Assignment Agency) does not define ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L12/24G16B40/20
CPCH04L41/142G16B40/20G16B40/00
Inventor 黄志忠
Owner ZTE CORP
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