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Modeling and data privacy protection method based on data map, information map and knowledge map

A technology of knowledge graph and data privacy, applied in the intersection of distributed computing and software engineering, it can solve the problem that it is difficult to effectively support data layer, query, abstraction, privacy addition and deletion cannot be carried out effectively, and there is no distinction between typed resources, etc. problems, to achieve the effect of enhancing integrity, eliminating redundancy, and enhancing consistency

Inactive Publication Date: 2018-11-13
HAINAN UNIVERSITY
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Technical problem: The existing demand modeling method does not distinguish typed resources, and various privacy resources are intertwined, it is difficult to effectively support query, abstraction, addition, deletion and modification on the data layer, information layer and knowledge layer, so Corresponding queries, abstractions, additions and removals of privacy cannot be done efficiently either

Method used

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  • Modeling and data privacy protection method based on data map, information map and knowledge map
  • Modeling and data privacy protection method based on data map, information map and knowledge map
  • Modeling and data privacy protection method based on data map, information map and knowledge map

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Embodiment Construction

[0048] The specific process of a modeling and data privacy protection method based on data graph, information graph and knowledge graph is as follows:

[0049] Step 1) corresponds to figure 1 As shown in 001, according to the needs of users, a framework based on data graphs, information graphs, and knowledge graphs is established;

[0050] Step 2) correspond to figure 1 As shown in 002, the privacy level L of data privacy resources according to formula 1 Privacy Determine the sequence of requirement description analysis;

[0051] Step 3) correspond to figure 1 As shown in 003, combine formula 2 and algorithm 1 to analyze the feasibility of privacy requirement description;

[0052] Step 4) correspond to figure 1 As shown in 004, combine formula 3 and algorithm 2 to analyze the consistency of privacy requirement description;

[0053] Step 5) correspond to figure 1 As shown in 005, combine formula 4 and algorithm 3 to analyze the redundancy of the privacy requirement descr...

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Abstract

The invention relates to a modeling and data privacy protection method based on a data map, an information map and a knowledge map, and belongs to the field of intersection of distributed calculationand software engineering. The modeling and data privacy protection method is mainly used for carrying out feasibility analysis, integrity analysis, consistency analysis and redundancy analysis on a demand of a user and extracting corresponding data stream, information stream, knowledge stream and control stream in each step of analysis to map to the data map, the information map and the knowledgemap. Then, on the basis of the demand of the user, data resources are classified into implicit and explicit cases according to existence of the data resources in a search space; and for implicit and explicit information privacy resources, the data privacy resources are converted into other types of privacy resources according to a sequence of influence sizes and all the related typed privacy resources are stored into a privacy space to carry out protection.

Description

technical field [0001] The invention is a modeling and data privacy protection method based on a data map, an information map and a knowledge map, and belongs to the cross field of distributed computing and software engineering. Background technique [0002] Knowledge graphs have emerged as a powerful tool for representing knowledge in the form of labeled directed graphs and giving semantics to textual information. Compared with UML classes, the knowledge graph has richer natural semantics, the expression mechanism is closer to natural language, and contains more and more complete semantic information. One of the reasons why UML is rarely used today to model automation applications is that UML lacks the formal semantics needed to model critical parts of an application. Moreover, UML does not distinguish typed resources, and various private resources are intertwined with each other, so it is difficult to effectively support query, abstraction, addition, deletion and modifica...

Claims

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Application Information

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IPC IPC(8): G06F21/64G06F21/62
CPCG06F21/64G06F21/6227G06F21/6245
Inventor 段玉聪张欣悦
Owner HAINAN UNIVERSITY
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