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Method and device for estimating network traffic entropy value based on median

A network flow, median technology, used in data exchange networks, digital transmission systems, electrical components, etc.

Active Publication Date: 2018-07-27
TSINGHUA UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to solve the above technical problems, the present invention provides a network traffic entropy estimation method and device based on the median, which can improve the accuracy of entropy estimation without increasing storage space and computational complexity

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  • Method and device for estimating network traffic entropy value based on median
  • Method and device for estimating network traffic entropy value based on median
  • Method and device for estimating network traffic entropy value based on median

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Embodiment Construction

[0089] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is only some embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0090] figure 1 It shows a schematic flow diagram of a method for estimating network traffic entropy value based on the median provided by an embodiment of the present invention, as shown in figure 1 As shown, the network traffic entropy estimation method based on the median in this embodiment is as follows.

[0091] 101. Obtain a data packet of...

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Abstract

The invention provides a median-based network flow entropy evaluation method and apparatus. The method includes the following steps: obtaining a data packet of network data flow and sending the data packet to slave nodes in a Storm cluster; receiving estimations value of an intermediate item S returned by the slave nodes, wherein the estimation values of the S are obtained through a preset entropy estimation algorithm by the slave nodes in the Storm cluster according to the received data packet; ordering the received estimation values of the S according to the magnitude; obtaining a median of the ordered estimation values of the S, taking the median as a final estimation value of the S; and obtaining an estimation value of an entropy of the network data flow according to the final estimation value of the S. In the method, the Storm cluster includes at least one salve node. The method increases the accuracy of entropy estimation while the storage space and the calculating complexity are not increased.

Description

technical field [0001] The invention relates to the technical field of network traffic analysis, in particular to a median-based method and device for estimating network traffic entropy. Background technique [0002] In the field of network traffic analysis, analysis based on flow distribution usually gets richer results than analysis based on simple flow. Entropy can well summarize and refine the characteristics of traffic distribution, and is an extremely important measure of network traffic. For example, many algorithms for network anomaly detection rely on the entropy value of network traffic. How to quickly and real-time calculate the entropy of network traffic on a high-speed backbone network is of great significance to fields such as anomaly detection, traffic engineering, and traffic analysis. To calculate the entropy value, it is necessary to record the size of each network flow. However, the traffic of the backbone network is very large. It is difficult to achiev...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L12/24
CPCH04L41/14
Inventor 杨家海王子玉李晨曦张世泽
Owner TSINGHUA UNIV
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