Intelligent network security analysis method, device and computer-readable storage medium

Abstract

The invention relates to an artificial intelligence technology, and discloses an intelligent network security analysis method. Perform processing operations including traffic segmentation, traffic cleaning and image generation to obtain a training traffic value, respectively input the request event and the training traffic value into the security analysis model for training and obtain a training loss value, until the training loss value is less than The third preset threshold is that the security analysis model exits the training, receives the user's request operation, uses the traffic detection center and the security analysis model in turn to obtain whether the user's request operation is a threat request event, and outputs the analysis result . The present invention also provides an intelligent network security analysis device and a computer-readable storage medium. The present invention can realize the precise and efficient intelligent network security analysis function.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence, and in particular, to a method, a device, and a computer-readable storage medium for receiving a user's request operation and performing intelligent network security analysis on the user's request operation. Background technique [0002] Computer network security mainly means that the business system will not be maliciously damaged during the operation of the network system, and the information resources and data resources will not be maliciously tampered with, thereby ensuring the information security of the computer system and users. As an effective protection method, the network traffic detection method can detect unknown attack behaviors and provide important technical support for ensuring the normal operation of business systems, and has received more and more attention in recent years. Traditional network traffic detection methods are mainly divided into four categor...

AI Technical Summary

Problems solved by technology

Among them, the accuracy of the port-based method is low, and the method based on deep packet inspection cannot deal with the problem of high computational complexity, while the statistics-based and behavior-based methods are based on the idea of ​​machine learning. Although the computational complexity is relatively low, However, it is necessary to design a set of feature sets that can accurately reflect the characteristics of traffic, so the quality of the feature set directly affects the classification performance.

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