Content push method and AI management and control system based on big data visualization mining processing

Abstract

The embodiments of the present application provide a content push method and an AI management and control system based on big data visualization mining processing, deep mining and learning from the example abnormal big data with the attribute carried by the first business operation vulnerability to the second method used to reflect the joint vulnerability variable business operation loopholes, so that vulnerability mining training can be carried out based on the second business operation loopholes and the first business operation loopholes at the same time, which is equivalent to learning the vulnerability feature variables of the first business operation loopholes and the vulnerability feature variables of the joint vulnerability variables at the same time. The mining model is configured based on the combination of the first vulnerability mining model and the second vulnerability mining model, so that the third vulnerability mining model obtained by the configuration can simultaneously learn the linkage vulnerability of the first service operation vulnerability and the second service operation vulnerability combined with the vulnerability variables. Feature variables can improve the accuracy of vulnerability mining and improve the reliability of targeted abnormal node traceability.

Description

technical field [0001] The present application relates to the field of big data technology, and in particular, to a content push method and an AI management and control system based on big data visualization mining processing. Background technique [0002] At present, with the rapid development of artificial intelligence technology, artificial intelligence technology has shown its application potential in some fields. For example, the application of artificial intelligence technology in vulnerability mining can greatly improve the current method of relying on rule matching and manual search for vulnerabilities. The problem of low mining efficiency. [0003] The abnormal log data generated in the process of business operation can usually reflect the characteristics of vulnerability expression to a certain extent. Therefore, the learning of vulnerability mining through abnormal log data has obvious value for vulnerability mining and later traceability of abnormal nodes. In th...

AI Technical Summary

Problems solved by technology

In the current artificial intelligence learning algorithm, usually only learn the vulnerability characteristic variables of independent dimensions, resulting in limited accuracy of business operation vulnerability mining, and also have a certain impact on the traceability of abnormal nodes in the later stage

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