A fine-grained access control method for massive graph data based on security labels

A technology of security labeling and access control, applied in the field of massive data processing, which can solve problems such as capacity and diversity characteristics that exacerbate security and privacy issues.
CN112699410BActive Publication Date: 2021-09-10BEIJING SCISTOR TECH
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Patents(China)
Current Assignee / Owner
BEIJING SCISTOR TECH
Publication Date
2021-09-10

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Abstract

The invention provides a fine-grained access control method for massive image data based on a security label, which belongs to the field of massive data processing. The method of the present invention includes: adding a security label to the point / edge / attribute storage structure and user information of the graph data to determine the security requirements required for access. The security label does not need to be defined in advance and is set after data generation or security design is completed ; When querying graph data, compare the user security label with the security label of the vertex / edge / attribute data to determine whether the user has permission to access the data. The security label of the present invention supports logical expression representation, adopts point, edge, and attribute three-level granularity security labels, and realizes security access control of different granularities; the present invention also uses bit operations to accelerate security label logic calculation and point / edge / attribute data filter calculation. The method of the invention greatly improves the security of mass image data access without sacrificing the graph data access performance.
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Description

technical field

[0001] The invention belongs to the technical field of mass data processing, and relates to a technical solution for performing fine-grained access control on mass key-value storage map data based on security labels. Background technique

[0002] The development of information and communication technology has opened up the era of the Internet of Everything. With the help of graph data processing technology in big data, the potential value of a large amount of related data in social, e-commerce, transportation, finance, Internet of Things and other industries can be tapped. Compared with traditional relational data, graph data is especially suitable for large-scale relationship analysis. It has the following characteristics: First, graph data adopts entity relationship modeling that is closer to the real world, which is intuitive and easy to understand, while relational data is more complex and abstract. Second, graph data query uses a way that is more suitabl...

Claims

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