Information security vulnerability classification method based on improved Bert model

Abstract

The invention relates to the technical field of information security and natural language processing, in particular to an information security vulnerability classification method based on an improved Bert model, which comprises the following steps: a, data preprocessing: collecting all vulnerability information data from a corpus as a data set, and preprocessing the data set in a filtering and cleaning mode, wherein the data set format is < vulnerability text description, vulnerability category >; dividing a data set into words as an input sequence X = (x1, x2,..., xn) in a word segmentation mode. According to the method, firstly, data is cleaned and filtered, noise data in a data set is removed, and the performance of an information security vulnerability classification model can be improved; secondly, a Bert model based on pre-training is introduced to classify vulnerabilities; and finally, adversarial training FGM is added to a word embedding layer, after a bidirectional encoder is added, techniques such as multi-sample dropout and label smoothing are added, so that the robustness and generalization ability of the model are improved, and the accuracy of vulnerability classification is further improved.

Description

technical field [0001] The invention relates to the technical field of information security and natural language processing, in particular to an information security vulnerability classification method based on an improved Bert model. Background technique [0002] With the rapid development of information technology, the application of the Internet and computers has penetrated into all aspects of human production and life. However, cybersecurity issues affect economic losses to countries, businesses and individuals. Therefore, the issue of network security has quickly attracted people's attention. At present, the number of vulnerabilities is growing rapidly, and it has become the main incentive to threaten the security of network and information systems. Due to the massive increase of new vulnerabilities, how to accurately and efficiently assess the threat level of security vulnerabilities in the network has become an important challenge in the field of network security an...

AI Technical Summary

Problems solved by technology

However, the training of the model by the above-mentioned deep learning method is limited to its own data set, lacks prior knowledge, and is prone to random initialization and overfitting.

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