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A CDN hosting node detection method based on graph semi-supervised classification

A node detection and semi-supervised technology, applied in the field of network security, can solve the problems of reducing available plaintext information, ignoring domain name and IP address structure information, lack of precision and recall, etc., to achieve a good effect of improvement

Active Publication Date: 2022-05-24
积至(海南)信息技术有限公司
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Problems solved by technology

[0009] The present invention provides a CDN hosting node detection method based on graph semi-supervised classification, which solves the problems of reducing available plaintext information, ignoring structural information of domain name and IP address, and lack of precision rate and recall rate in the existing CDN hosting node detection method The problem

Method used

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  • A CDN hosting node detection method based on graph semi-supervised classification
  • A CDN hosting node detection method based on graph semi-supervised classification
  • A CDN hosting node detection method based on graph semi-supervised classification

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Embodiment Construction

[0056] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0057] Please refer to figure 1 , figure 2 , image 3 , Figure 4 , Figure 5 and Image 6 ,in, figure 1 A flow chart of a preferred embodiment of the method for detecting CDN hosting nodes based on graph semi-supervised classification provided by the present invention;

[0058] figure 2 For the comparison of the structural drawings in the present invention; image 3 The three-dimensional diagram of the cooling device used for server cooling when the CDN hosting node is detected provided by the present invention; Figure 4 for image 3 a top view of the whole shown; Figure 5 for image 3 The schematic diagram of the structure inside the submersible tank shown; Image 6 for Figure 5 Enlarged view of section A shown.

[0059] A CDN managed node detection method based on graph semi-supervised classification includes the following processes:...

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Abstract

The invention provides a CDN hosting node detection method based on graph semi-supervised classification. The CDN hosting node detection method based on graph semi-supervised classification includes the following processes: S1 graph construction; S2 feature extraction and vertex labeling; S3 graph vertex classification for feature information and structural information after the step S2 vertex labeling. The CDN hosting node detection method based on graph semi-supervised classification provided by the present invention has a semi-supervised learning process that can combine the feature information of marked vertices and unmarked vertices, so that the evaluation index of the classification result is better than multiple traditional machine learning classification methods. Through automatic browsing and capturing of Alexa's top 100,000 domain names to obtain active data and conduct experiments, it is confirmed that the results are indeed higher than multiple traditional models ranging from 3% to 18%, and the improvement in recall rate is the best.

Description

technical field [0001] The invention relates to the field of network security, in particular to a CDN hosting node detection method based on graph semi-supervised classification. Background technique [0002] A Content Delivery Network (CDN) is a distributed server network consisting of proxy servers and data centers that provides users with high performance, scalability, and Low-cost network content, as the key infrastructure of the Internet, CDN is currently widely deployed, however, along with the wide application of CDN, some malicious and abuse problems also occur. Therefore, identifying CDN hosting nodes from network traffic is important for Quality of Service (QoS), malware detection and firewall rule settings are all critical. [0003] Most of the current CDN managed node detection methods rely on analyzing plaintext data in network traffic data, and the most commonly used methods are active detection and scanning. At the same time, the filtering and analysis of pa...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V10/764G06K9/62H04L9/40
CPCH04L63/1416H04L63/1408G06F18/214G06F18/241
Inventor 郑超马小青彭宣正戚岱杰
Owner 积至(海南)信息技术有限公司
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