A method and device for detecting multiple types of application layer DDOS attacks
An application layer and type technology, applied in the Internet field, can solve the problem of inability to detect specific types of application layer DDoS, and achieve the effect of improving detection accuracy, reducing malicious traffic, and improving accuracy.
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Embodiment 1
[0047] A structural diagram of a device that can detect multiple types of application layer DDoS attacks provided by an embodiment of the present invention is as follows: figure 1 As shown, it includes: feature generation module, offline training module and online detection module.
[0048] The feature generation module 10 is configured to generate valid feature information suitable for various types of application layer DDoS attacks, and transmit the valid feature information to the offline training module.
[0049] The offline training module 20 is used to train and obtain various types of application layer DDoS attack detection models according to the effective feature information, and use the detection sample set to train and verify the various types of application layer DDoS attack detection models.
[0050] The online detection module 30 is used for deploying the trained multiple types of application layer DDoS attack detection models, using multiple types of application...
Embodiment 2
[0096] Figure 5 A schematic diagram of the work flow of a device that can detect multiple types of application-layer DDoS attacks online provided by an embodiment of the present invention. The specific processing flow includes: a stage of online capture of traffic at the network entrance, and a real-time traffic capture tool is used to obtain detection at the network traffic entrance. Traffic; in the online feature generation stage, the generated traffic files are read online, and the flow feature extraction tool is used to generate the corresponding detection sample set; in the online prediction stage, the effective feature information screened in the feature analysis stage is selected as input, and the trained application layer The DDoS attack detection model performs online prediction on the experimental traffic to be detected.
[0097] Optionally, use the SHELL script under the system to realize the automated process of online traffic capture, feature generation, and onli...
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