DNA generation and verification method for data object

Abstract

The invention relates to a DNA generation and verification method for a data object. The method is characterized by comprising the following steps of S1, defining the data object and a version numbercalculation method thereof; S2, mapping the data object into Hash values with the same length based on a Hash function, and checking the integrity of the data object; S3, generating DNA of the data object by using the Hash value of the data object, the DNA value of the parent version of the data object and the version number; and S4, tracing to the DNA of the previous version or the root version of the current data object by utilizing the DNA and the Hash value of the current data object. The method can be widely applied to the fields of auditing data continuity and the like.

Description

technical field [0001] The invention relates to a method for generating and verifying DNA of a data object, and relates to the field of data management. Background technique [0002] In the era of big data, data types are more abundant and diverse, including a series of forms such as values, texts, pictures, videos, and rich media, which also cause a series of problems such as fragmented data, data islands, garbage data, and data out of control. bring many new problems. Analyzing the process of data generation and evolution can accurately evaluate the quality and correctness of data objects, solve the problem of traceability of controversial data, and help a series of problems such as data islands, garbage data, and data out of control. Therefore, the study of data lineage is of great importance. significance. [0003] At present, the application fields of data lineage mainly use mapping and tracking technologies to manage lineage in databases, data warehouses, P2P and oth...

AI Technical Summary

Problems solved by technology

[0003] At present, the application fields of data lineage mainly use mapping and tracking technologies to manage lineage in databases, data warehouses, P2P and other data processing frameworks, such as SPIDER, Trio, DBNotes, etc., all of which have the following problems: 1) Data lineage management mainly relies on platforms It is still a relational database, but the current data objects have many types and lack of correlation, and the current means cannot adapt to the new form of data objects; 2) The data lineage is mainly completed by adding lineage relationship annotations, but it is easy to be tampered with, which may cause data traceability Error; 3) The lineage traceability method is expensive, and additional storage space is required for annotations

In the traditional version number calculation method, each data object has only one version number, only the content has a version number or the content and metadata are put together for version number calculation, and only the numerical value is used to represent the version change, resulting in the following problems: 1) It cannot distinguish between changes in data content and metadata; 2) It can only record version changes, but the reason for the changes is unknown; 3) It is only applicable to manual identification, which will cause a lot of waste of manpower

[0004] The existing methods of existing data lineage cannot meet the current requirements for lineage management of data objects, mainly as follows: 1) cannot process non-relational data such as text, pictures, videos, and rich media; 2) cannot use computers to identify data objects version, and the reasons why version changes cannot be intuitively reflected; 3) data lineage annotations are easy to be tampered with, and cannot meet the requirements of data anti-forgery and tampering; 4) too high overhead, not suitable for the current massive data and data forms

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