Fine particle data protection method based on security model

Abstract

The invention provides a fine particle data protection method based on a security model. The method comprises the following steps: step 1, establishing a data model; step 2, generating a protection rule and binding the protection rule with the data model to generate a security model; step 3, establishing association mapping from the data to the security model; 4, extracting data according to the association mapping relation between the data and the security model to form security model data; and 5, executing the protection rule through the security model to complete data protection. According to the scheme provided by the invention, unified protection measures are provided for common data through the security model, the consistency of data protection strength is guaranteed, and the problem of data leakage caused by a certain protection short board condition is avoided; the security model performs integrity and authenticity protection based on a cryptographic algorithm, and has relatively strong tamper-proof and anti-counterfeiting capabilities; the complexity of data security configuration management is greatly simplified, the professional technical threshold of data security management is reduced, and the efficiency and security of data protection are improved.

Description

technical field [0001] The invention relates to the field of data protection, in particular to a fine-grained data protection method based on a security model. Background technique [0002] In the scenarios of big data applications and cross-domain data sharing, there is a large demand for structured and semi-structured data protection. The current method for structured and semi-structured data protection depends on the granularity of data protection. There are two main methods: 1) Configure the same data protection rules for the same type of data, and implement data encryption and access control. Data can be processed in batches, but the granularity of data protection is relatively coarse. 2) Extract structural information from the specified structured and semi-structured data, then configure protection rules for the structural information, and perform encryption and access control on the data associated with the structural information according to the protection rules. I...

AI Technical Summary

Problems solved by technology

[0003] In order to avoid data leakage, it is usually necessary to adopt data protection strength and protection granularity that meet the security requirements. Protection rule configuration requires a high level of administrators, and professional data security personnel are usually required for operation and maintenance management. In the actual production environment, because Factors such as cost and management are difficult to implement

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