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p2p network traffic detection method

A technology of P2P network and traffic detection, which is applied in the direction of data exchange network, digital transmission system, electrical components, etc., can solve the problems of poor detection accuracy, achieve good accuracy and stability, good stability and robustness, and improve The effect of detection accuracy

Inactive Publication Date: 2011-12-21
NORTHWESTERN POLYTECHNICAL UNIV
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AI Technical Summary

Problems solved by technology

[0009] In order to overcome the shortcomings of poor detection accuracy of existing network traffic detection methods, the present invention provides a P2P network traffic detection method

Method used

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Examples

Experimental program
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Embodiment Construction

[0031] 1. Network traffic capture.

[0032] Use the traffic collection card to capture network traffic at the gateway exit, analyze the captured network traffic, and calculate the corresponding flow statistics. Only capture the traffic whose transmission protocol is TCP, the period is one week, and save it in PCAP file format.

[0033] 2. Network flow reorganization.

[0034]According to the source IP address, source port, transmission protocol, destination port, and destination IP address of the network data packet, the network flow is reassembled. These five data packets with the same information form a data flow. Use 17-filter to mark the reorganized network flow, and mark data into two types: P2P protocol and non-P2P protocol.

[0035] 3. Extract statistical features.

[0036] A total of 20 statistical features are extracted in units of data streams. Including packet size, packet arrival time interval, flow size, flow duration, etc. The protocol-known data flow is add...

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Abstract

The invention relates to a traffic detection method for a peer-to-peer (P2P) network. The method is used for solving the technical problem of low detection accuracy of the conventional network traffic detection method. The technical scheme is that: a classifier is trained in two stages, a value of a positive instance sample number N in a test sample is approximately estimated by using semi-supervised clustering, and a two stage variable model (TSVM) is further trained according to the value of N. Compared with a background technology, the invention makes the value of N closer to a true value, endows the trained classification TSVM with high stability and robustness and improve network traffic detection accuracy. A great amount of unmarked data takes part in the training of the classification model, and the advantages of semi-supervised learning are fully utilized; therefore, compared with a conventional supervised learning algorithm in which the model is trained only by marked data, the method is higher in accuracy and stability.

Description

technical field [0001] The invention relates to a network flow detection method, in particular to a P2P (peer-to-peer) network flow detection method. Background technique [0002] With the wide application of P2P network technology, the proportion of P2P network traffic on the domestic backbone network has surged from 0.76% in the past to about 70%. Therefore, the identification and control of P2P traffic is of great significance for improving network service quality and network management and maintenance. [0003] The traditional P2P traffic detection mainly adopts the DPI (Deep Packet Inspection) method, and the DPI method has obvious limitations. The DPI method detects based on the feature field in the application layer of the message, and has two defects: on the one hand, the DPI method can only identify P2P traffic with known protocol characteristics; on the other hand, it cannot identify the traffic of the encrypted protocol, and involves to the issue of violating us...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L12/26H04L29/08
Inventor 丁要军蔡皖东
Owner NORTHWESTERN POLYTECHNICAL UNIV
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