Machine learning, privacy code determination method, device and electronic equipment

Abstract

The embodiment of this specification discloses a method, device, and electronic device for machine learning and privacy code determination, wherein, the machine learning method can acquire batches of sample data including positive and negative samples, the positive sample data includes privacy code files, and the negative The sample data does not contain privacy code files; based on the similarity measurement parameters of the code files, a plurality of first code files are screened out from the sample data, and the code files are screened out from a preset code library whose privacy labels are known A plurality of second code files; based on the plurality of first code files and the plurality of second code files, determine the target parameters corresponding to the sample data; combine the target parameters corresponding to the sample data and the sample data The label of is used as input to train the target model, and the target model is used to determine the similarity measurement parameters between a batch of code files to be detected and private code files.

Description

technical field [0001] The present application relates to the field of computer technology, and in particular to a method, device and electronic equipment for machine learning and privacy code determination. Background technique [0002] Code is an important asset of a computer program product development company and needs to be protected, especially the privacy code of the company's core system. However, the codes of the development company are various and large in number, and may also contain a lot of non-private codes, such as open source codes and general testing codes. Therefore, if code protection is to be performed, it is first necessary to identify which codes belong to privacy codes, and then provide targeted protection. [0003] At present, preliminary screening is performed based on the code file name, and then the relevant content in the code is manually checked to determine the privacy code that needs to be protected. Obviously this way of determining is ineff...

AI Technical Summary

Problems solved by technology

[0004] The embodiment of this specification provides a method, device, and electronic device for machine learning and privacy code determination to solve the problem of low efficiency in the way of determining privacy codes in related technologies

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