Data security grading classification method based on deep learning

Abstract

The invention provides a data security grading and classification method based on deep learning, and relates to the technical field of data security grading and classification, and the method comprises the following steps: 1, collecting business data, obtaining a plurality of groups of security data flow direction sequence combinations, and carrying out grading and marking; 2, extracting flow direction sequence combination features of the security data flow; 3, constructing a data security grading mature model based on deep learning; and 4, performing real-time dynamic monitoring on internal and external data streams which are occurring in the service information system by using the data security grading model, extracting a complete / incomplete dynamic data information stream sequence group for classification, and forming a data security grading result of the A core data, the B important data and the C general data until the group of operation behaviors is finished. Through the method provided by the invention, automatic grading of the service information system data can be realized, real-time grading and scene classification are carried out on mass data with mass data categories in real time, and the working efficiency of a data administrator is improved.

Description

technical field

[0001] The invention belongs to the technical field of data security classification and classification, in particular to a data security classification classification method based on deep learning. Background technique

[0002] The predecessor of deep learning is machine learning, and machine learning is a method of realizing artificial intelligence. It involves the field of big data, and big data involves all aspects of finance and IT. At its most basic, machine learning uses algorithms to parse data, learn from it, and then make decisions and predictions about real-world events. Unlike traditional software programs that are hard-coded to solve specific tasks, machine learning is "trained" with a large amount of data, using various algorithms to learn from the data how to complete the task. Deep learning is an emerging technology in recent years. Deep learning is not an independent learning method. It also uses supervised and unsupervised learning methods t...

Examples

Embodiment Construction

[0035] Below in conjunction with accompanying drawing, the present invention is described in further detail:

[0036] In the present invention, by combining massive amounts of graded and classified data calibrated in business application scenarios, the massive amounts of original data are continuously classified (for example, undergraduate-related information, graduate-related information, faculty-related information, etc.), and then the classified data is processed. Deep learning grading and calibration evaluation form a mature data security grading model, and the obtained mature data security grading model can be used to grade the real-time massive data and output the graded and classified data stream.

[0037] First, classify the security level of a set of business data streams: A core data; B important data; C general data.

[0038] The original business data source indicates that the data source of the entire data flow is located within the business information system.

...

technical field

[0001] The invention belongs to the technical field of data security classification and classification, in particular to a data security classification classification method based on deep learning. Background technique

[0002] The predecessor of deep learning is machine learning, and machine learning is a method of realizing artificial intelligence. It involves the field of big data, and big data involves all aspects of finance and IT. At its most basic, machine learning uses algorithms to parse data, learn from it, and then make decisions and predictions about real-world events. Unlike traditional software programs that are hard-coded to solve specific tasks, machine learning is "trained" with a large amount of data, using various algorithms to learn from the data how to complete the task. Deep learning is an emerging technology in recent years. Deep learning is not an independent learning method. It also uses supervised and unsupervised learning methods t...

Examples

Embodiment Construction

[0035] Below in conjunction with accompanying drawing, the present invention is described in further detail:

[0036] In the present invention, by combining massive amounts of graded and classified data calibrated in business application scenarios, the massive amounts of original data are continuously classified (for example, undergraduate-related information, graduate-related information, faculty-related information, etc.), and then the classified data is processed. Deep learning grading and calibration evaluation form a mature data security grading model, and the obtained mature data security grading model can be used to grade the real-time massive data and output the graded and classified data stream.

[0037] First, classify the security level of a set of business data streams: A core data; B important data; C general data.

[0038] The original business data source indicates that the data source of the entire data flow is located within the business information system.

...

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