Peer-to-peer network traffic feature selection method based on cuckoo search algorithm

A cuckoo search algorithm and peer-to-peer network technology, applied in the field of network traffic identification and network traffic feature selection, to improve efficiency and accuracy, and save computing time

Inactive Publication Date: 2014-10-08
HUBEI UNIV OF TECH
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Commonly used solving algorithms such as branch and bound method and ba

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  • Peer-to-peer network traffic feature selection method based on cuckoo search algorithm
  • Peer-to-peer network traffic feature selection method based on cuckoo search algorithm
  • Peer-to-peer network traffic feature selection method based on cuckoo search algorithm

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Embodiment Construction

[0038] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0039] please see figure 1 , figure 2 , the technical scheme adopted in the present invention is: a kind of peer-to-peer network traffic feature selection method based on cuckoo search algorithm, it is characterized in that, comprises the following steps:

[0040] Step 1: Use the network packet capture tool to randomly capture a certain number of network data packets in different periods of time and store them in the sample database, manually analyze the number of peer-to-peer network packets and ordinary network packets, and extract network traffic from th...

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Abstract

The invention discloses a peer-to-peer network traffic feature selection method based on a cuckoo search algorithm. A peer-to-peer network traffic feature selection problem is solved in an optimized mode through the cuckoo search algorithm so that an optimal feature subset of essential attributes of peer-to-peer network traffic can be fast obtained, and the peer-to-peer network traffic feature selection method can be used in the technical field relevant to peer-to-peer network traffic recognition and mode recognition. A high-quality feasible solution for the feature selection problem can be found within an acceptable time cost through the method, feature dimensions to be selected do not need to be specified manually, good balance between the correct recognition rate and the feature dimensions can be intelligently achieved, and an appropriate optimal feature subset can be automatically found. According to the peer-to-peer network traffic feature selection method, features of an original data set in a peer-to-peer network are selected through the cuckoo search algorithm, irrelevant or redundant peer-to-peer network traffic features are removed, really relevant features are obtained, the calculation time for extracting features during peer-to-peer network traffic recognition is saved, and thus the efficiency and the accuracy of peer-to-peer network traffic recognition are improved.

Description

technical field [0001] The invention belongs to the field of cross-application of intelligent computing, computer network and pattern recognition, relates to the application of pattern recognition method in computer network, especially relates to the peer-to-peer network flow recognition problem of this technology in computer network, and specifically relates to a peer-to-peer network based on cuckoo search algorithm Network traffic feature selection method. Background technique [0002] Peer-to-peer network technology is an Internet system that has no central server and relies on user groups to exchange information, and is an important branch of Internet technology. Unlike a central network system with a traditional central server, each client of a peer-to-peer network is both a client machine and a server. At present, peer-to-peer network technology is widely used in military, commercial, government information, communication and many other fields. The US "Fortune" magaz...

Claims

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Application Information

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IPC IPC(8): H04L12/801
Inventor 叶志伟李沁沄王明威王春枝刘伟陈宏伟徐慧宗欣露尹宇洁喻东阳
Owner HUBEI UNIV OF TECH
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