Training method of network security situation model, recognition method and recognition device

Abstract

The invention belongs to the technical field of the computer network security and machine learning, and specifically relates to a training method of a network security situation model, a recognition method and a recognition device. The training method of the network security situation model comprises the following steps: S101, acquiring network data; S102, extracting a network data sample from the network data; S103, processing the extracted network data sample, analyzing the network data to obtain an attribute value of the network data, and judging whether the attribute value of the network data is safely corresponding to the network data; S104, analyzing and processing the attribute value of the network data to obtain a feature vector of the attribute value of the network data; and S105, determining a parameter of linear classifier through the feature vector of the attribute value of the network data.

Description

technical field [0001] The invention belongs to the technical fields of computer network security and machine learning, and in particular relates to a network security situation model training method, an identification method and an identification device. Background technique [0002] In recent years, with the advent and popularization of the era of mobile Internet and smart terminals, people's online behaviors have become more frequent, and the scale of marketing has become larger and larger. Various social networks have formed a complex, heterogeneous large-scale network. However, due to the characteristics of mobility, scalability, large-scale, and ubiquity of communication networks, while the network penetrates into people's social life, it has also become the primary target of hacker attacks, resulting in a continuous and rapid increase in the number of network security vulnerabilities. Therefore, the security problem will definitely become the primary problem to be sol...

AI Technical Summary

Problems solved by technology

However, it is precisely because of the above-mentioned characteristics of the Internet that many security problems have arisen: leakage, pollution, uncontrollable

[0005] The above-mentioned referenced patent documents all use neural network algorithms for the analysis and prediction of the network security situation, and the neural network algorithms have the following disadvantages: 1. The local minimization problem leads to different results for each training; 2. The neural network algorithm Slow convergence speed; 3. The choice of neural network structure is different; 4. There is a certain contradiction between the prediction ability and training ability of neural network

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