Sensitive data detection cloud service method and cloud service platform
A technology for sensitive data and cloud services, applied in unstructured text data retrieval, electronic digital data processing, natural language data processing, etc. The effect of reducing costs and barriers
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Embodiment 1
[0068] see figure 1 Step diagram, a method for sensitive data detection cloud service of the present invention, comprises the following steps:
[0069] S01, the enterprise uploads training samples;
[0070] Through the data interface opened by the service provider, the enterprise uploads the training samples to the service provider.
[0071] The training samples mentioned above refer to the internal document set provided by the enterprise, and the enterprise needs to provide a document set similar to its content according to the type of sensitive data that it hopes to find on the Internet. Training sample file formats include but are not limited to Office files (docx / elsx / pptx / csv), scripts (sh / sql / java), web pages (html / css), data (json / log), text (txt), etc.
[0072] S02, the server uses training samples to perform model training to generate a target model;
[0073] This step is the core step, see figure 2 , using AI technologies in the field of natural language process...
Embodiment 2
[0099] see image 3 , the present invention also discloses a sensitive data detection cloud service platform, which integrates powerful document collection capabilities and model service capabilities by deploying collectors and models on the cloud. combine Figure 4 , the business process of the cloud service platform to provide services to enterprises includes the following core modules:
[0100] Data interface module: used for enterprises to upload training samples;
[0101] Model training module: used for model training using training samples to obtain Bert+BiLSTM classification model;
[0102] Model prediction module: used to use the model to predict Internet documents and obtain prediction results;
[0103] The prediction result return module is used to return the suspected documents in the prediction result to the enterprise.
Embodiment 3
[0105] On the basis of Embodiment 1 and Embodiment 2, this embodiment provides a storage medium in which multiple instructions are stored, and the instructions are suitable for being loaded and executed by a processor, and the multiple instructions are:
[0106] Data interface for enterprises to upload training samples;
[0107] Model training, which is used to perform model training using training samples to generate a target model; the specific execution process of this instruction is:
[0108] see figure 2 , using AI technologies in the field of natural language processing, including Bert and BiLSTM, the entire modeling process can be fully automated without human intervention.
[0109] Because the model to be established belongs to the predicted classification model, it is necessary to establish a positive and negative sample set. The training samples provided by the enterprise are used as positive samples. Negative samples can be created with any other document set, as ...
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