Network attack detection method, device and equipment and storage medium

Abstract

The invention discloses a network attack detection method, device and equipment and a storage medium, and belongs to the technical field of networks. The invention provides a scheme for detecting a network attack based on multi-dimensional features. An integrated learning mode is adopted. Through the multiple classification models, whether the data flow is abnormal or not is judged according to the features of the multiple dimensions, then the classification results of the multiple dimensions are summarized to comprehensively judge whether the network attack occurs or not, the considered features are more diversified, the method can adapt to diversified service forms of an existing network, and the accuracy of detecting the network attack is improved.

Description

technical field [0001] The invention relates to the field of network technology, in particular to a network attack detection method, device, equipment and storage medium. Background technique [0002] With the development of network technology, incidents of network attacks on the Internet are becoming more and more frequent. Network attacks cause problems such as slow access and connection interruptions on the server, resulting in the failure of the server to provide services normally. Therefore, it is necessary to detect network attacks in time to deal with them. and defend against cyber attacks. [0003] At present, the process of network attack detection is usually: manually setting the traffic threshold based on experience, and pre-store the traffic threshold in the computer device. During the operation of the current network, the computer equipment will obtain the data flow sent to the server, count the flow of the data flow, and compare the flow with the flow threshol...

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Problems solved by technology

[0005] The embodiment of the present invention provides a network attack detection method, device, equipment and st

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