A method for restoration and detection of structured sensitive data based on big data

Abstract

The present invention relates to the field of information security technology. The present invention discloses a method for restoring and detecting structured sensitive data based on big data, including structured data extraction, knowledge representation and knowledge map construction, and sensitive data restoration. The structured data extraction is aimed at Structured data in databases and text files are aggregated and extracted according to data standards. The final form of data aggregation is a relational database, and then the data is converted into RDF format; knowledge representation and knowledge map construction are knowledge elements obtained from different data sources Carry out fusion to build the relationship between the data to form a knowledge map; sensitive data restoration is to extract the associated data from the aggregated data according to the standard configuration, import the data into the associated database according to the relationship of the knowledge map, and then perform sensitive data restoration query. The invention solves the problems that it is impossible to detect whether the massive structured sensitive data is restored after desensitization in the big data environment, and it is impossible to evaluate the leakage of sensitive data.

Description

technical field [0001] The invention relates to the technical field of information security, in particular to a method for restoring and detecting structured sensitive data based on big data. Background technique [0002] In the big data environment, data is frequently shared and exchanged, and there are more and more government and enterprise data circulation transactions. In order to protect privacy, the structured stored data is deprived and transmitted to the network. This is currently the most commonly used method for data privacy protection. However, with the generation of massive data, data from diverse sources converges to the big data center, and after these structured data are fused in a certain way, it is possible to restore sensitive data. [0003] Existing technical research mainly focuses on how to de-private sensitive data to ensure the security of sensitive data in a single use case, but ignores the problem of structured sensitive data leakage after sensitiv...

AI Technical Summary

Problems solved by technology

However, with the generation of massive data, data from diverse sources converge into the big data center, and after these structured data are fused in a certain way, sensitive data may be restored

[0003] Existing technical research mainly focuses on how to de-private sensitive data to ensure the security of sensitive data in a single use case, but ignores the problem of structured sensitive data leakage after sensitive data is aggregated. Research on reduction detection

Therefore, there is an urgent need for a method for detecting structured sensitive data restoration based on big data to solve the problems that the restoration of structured sensitive data cannot be detected and the degree of leakage cannot be evaluated in a big data environment.

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