Data processing method, apparatus, device and readable storage medium

Abstract

The present application discloses a data processing method, device, device, and readable storage medium, and relates to deep learning technology in the field of artificial intelligence. degree, obtain N target feature dimensions from the k feature dimensions; obtain the target sample vulnerability features corresponding to the target sample vulnerability data under the N target feature dimensions, and input the N target sample vulnerability features into the initial vulnerability detection model for prediction , obtain the target sample prediction result for the vulnerability attribute category; adjust the parameters of the initial vulnerability detection model based on the target sample prediction result and the target sample label of the obtained target sample vulnerability data, and obtain the vulnerability detection model. By adopting the present application, the association relationship between vulnerability data and vulnerability attribute categories can be more accurately determined, and the efficiency of vulnerability detection of vulnerability data can be improved.

Description

technical field [0001] The present application relates to the field of Internet technologies, and in particular, to a data processing method, apparatus, device, and readable storage medium. Background technique [0002] With the advent of the digital age, more and more occasions will be applied to information data transmission technology, and people have higher and higher requirements for the security of data transmission. Data security detection generally establishes, accumulates, and matches detection rules based on known traffic attacks. Common security detections include firewall technology that relies on rule stacking to form a database. [0003] These security detection technologies relying on the accumulation of rules have lower learning costs. The number of rules of these rule accumulation technologies is increasing, the similar rules between the rules cannot be identified, and there is redundancy between the rules. The number of rules of these security detection t...

AI Technical Summary

Problems solved by technology

The number of rules in these rule accumulation technologies is increasing, similar rules between rules cannot be identified, and there is redundancy between rules. The number of rules in these security detection technologies is usually large, and the large number of rules in these technologies will lead to Rules interact with each other, which increases the human maintenance cost of adding and modifying rules, and reduces the efficiency of model testing

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