CN-120655162-B - Enterprise data asset management method and system based on block chain

CN120655162BCN 120655162 BCN120655162 BCN 120655162BCN-120655162-B

Abstract

The invention relates to the technical field of data processing, in particular to a block chain-based enterprise data asset management method and system, comprising the steps of acquiring each business module of enterprise asset data stored in each side chain; and under the initial storage strategy, analyzing the load change condition of the corresponding side chain according to the memory use condition and bandwidth information of each side chain at each updating moment, and adjusting the synchronization degree of each side chain at each updating moment in real time by combining the updating condition of the side chain at the historical updating moment to determine the global storage strategy of the block chain structure. The invention can effectively improve the response speed and management efficiency of enterprise data asset management.

Inventors

SHI HUIMIN
XIN XIAO
TIAN MAOJIN
CHI WEI
ZHAO SHIPENG
LIU PU
GAO XINYU
GUO SHUAI

Assignees

山东未来数据科技有限公司

Dates

Publication Date: 20260508
Application Date: 20250616

Claims (9)

1. A blockchain-based enterprise data asset management method, the method comprising the steps of: Acquiring each business module with enterprise asset data stored in each side chain; Combining the core difference condition between each business module in each side chain and each business module in other side chains according to the interaction information between the data contained in different business modules, and carrying out merging operation on the side chains to determine an initial storage strategy of a block chain structure, wherein the initial storage strategy comprises the steps of acquiring a confidentiality marking value, an access frequency and an update frequency of each type of enterprise data in enterprise asset data, obtaining a core degree index of each type of enterprise data according to the confidentiality marking value of each type of enterprise data, the access frequency and the update frequency of all enterprise data of the same type, obtaining a data dependency degree between any two different business modules according to the interaction frequency between any two different business modules and the repetition condition of an interaction object with each business module, and obtaining the data merging degree between any two different business modules according to the difference condition of the core degree index between any two different business modules; Under the initial storage strategy, according to the memory use condition and bandwidth information of each side chain at each updating moment, the load change condition of the corresponding side chain is analyzed, the synchronization degree of each side chain at each updating moment is adjusted in real time by combining the updating condition of the side chain at the historical updating moment, and the global storage strategy of the block chain structure is determined.
2. The blockchain-based enterprise data asset management method of claim 1, wherein the acquiring each business module in which the enterprise asset data is stored in each side chain, specifically comprises: Dividing the enterprise data with different core grades according to the different change conditions of the core index among the enterprise data with different types; Enterprise data belonging to the same service and the same core class are used as the same service module, different types of enterprise data contained in each service module are stored in side chains, and one side chain at least comprises one service module.
3. The blockchain-based enterprise data asset management method according to claim 2, wherein the obtaining the core index of each type of enterprise data according to the confidentiality flag value of each type of enterprise data, the access frequency and the update frequency of all enterprise data of the same type specifically comprises: determining a first importance coefficient corresponding to each type of enterprise data based on the confidentiality marking value of each type of enterprise data and the average value of the access frequencies of all enterprise data of the same type; Determining a second important coefficient corresponding to each type of enterprise data based on a difference between a maximum value of update frequencies of all types of enterprise data and a mean value of update frequencies of all types of enterprise data; and obtaining the core index of each type of enterprise data according to the first important coefficient and the second important coefficient.
4. The blockchain-based enterprise data asset management method according to claim 2, wherein the classifying the enterprise data of different core levels according to the variation of the core index difference between the enterprise data of different types specifically comprises: the core indexes of all types of enterprise data are arranged according to a preset sequence to obtain a core sequence; Determining a grading reference value corresponding to each core difference value based on the ratio between each core difference value and the average value of all the core difference values; And according to the sequence from large to small, acquiring the positions corresponding to the preset number of grading reference values as the dividing points, and dividing the core degree sequence to obtain that the enterprise data of the corresponding type of each data segment belongs to a core grade.
5. The method for managing enterprise data assets based on blockchain as in claim 1, wherein the obtaining the data dependency degree between any two different business modules according to the interaction frequency between any two different business modules and the repetition of the interaction object having interaction operation with each business module specifically includes: acquiring any two different service modules as a first service module and a second service module respectively; Acquiring all different service modules which have interactive operation with a first service module to form a first interactive set, and acquiring all different service modules which have interactive operation with a second service module to form a second interactive set; And determining the data dependency degree of the first service module and the second service module based on the number of service modules contained in the intersection of the first interaction set and the second interaction set and the interaction frequency between the first service module and the second service module.
6. The method for managing enterprise data assets based on blockchain as in claim 5, wherein the combining the data dependency according to the difference of core indexes between any two different service modules to obtain the data merging degree between any two different service modules specifically includes: And determining a similar characteristic factor based on the difference between the average core index of all types of enterprise data contained in the first service module and the average core index of all types of enterprise data contained in the second service module, and taking the normalized value of the product of the data dependency degree of the first service module and the second service module and the similar characteristic factor as the data merging degree between the first service module and the second service module.
7. The method for managing enterprise data assets based on blockchain as in claim 1, wherein analyzing the load change of the corresponding side chain according to the memory usage and bandwidth information of each side chain at each update time, and adjusting the synchronization degree of each side chain at each update time in real time in combination with the update of the side chain at the historical update time, determining the global storage policy of the blockchain structure specifically comprises: acquiring the memory occupancy rate and the residual bandwidth occupancy rate of each side chain at each updating moment; Analyzing the load conditions of the corresponding side chains according to the memory occupancy rate and the residual bandwidth occupancy rate, and combining the change degree of the load conditions of each side chain at adjacent updating moments to obtain the dynamic load weight of each side chain at each updating moment; For any side chain, the ratio of the dynamic load weight of each updating moment to the dynamic load weight of the adjacent previous historical updating moment is taken as an adjustment coefficient, and the adjustment coefficient is utilized to adjust the synchronous time interval of the historical updating moment to obtain the adjustment time interval of each updating moment, wherein the time interval is used for representing the data synchronous frequency between the corresponding side chain and the main chain.
8. The method for managing enterprise data assets based on blockchain as in claim 7, wherein analyzing the load condition of the corresponding side chain according to the memory occupancy rate and the residual bandwidth occupancy rate, combining the change degree of the load condition of each side chain at the adjacent update time to obtain the dynamic load weight of each side chain at each update time, specifically includes: For any side chain, obtaining a load coefficient of the side chain at each updating moment according to the memory occupancy rate of the side chain at each updating moment and the residual bandwidth occupancy rate, wherein the memory occupancy rate and the load coefficient are in positive correlation, and the residual bandwidth occupancy rate and the load coefficient are in negative correlation; And adjusting the load coefficient of each updating moment by utilizing the ratio of the load coefficient of the side chain at each updating moment to the load coefficient of the adjacent previous historical updating moment to obtain the dynamic load weight of the side chain at each updating moment, wherein the dynamic load weight is a normalized numerical value.
9. A blockchain-based enterprise data asset management system for implementing the steps of a blockchain-based enterprise data asset management method as claimed in any of claims 1 to 8, said blockchain-based enterprise data asset management system comprising in particular: the data acquisition module is used for acquiring each business module of the enterprise asset data stored in each side chain; The initial strategy analysis module is used for combining the side chains according to the interaction information between each service module in each side chain and each service module in other side chains and combining the core difference condition among the data contained in different service modules, so as to determine the initial storage strategy of the block chain structure; And the global strategy analysis module is used for analyzing the load change condition of the corresponding side chain according to the memory use condition and bandwidth information of each side chain at each updating moment under the initial storage strategy, and determining the global storage strategy of the block chain structure by adjusting the synchronization degree of each side chain at each updating moment in real time in combination with the updating condition of the side chain at the historical updating moment.

Description

Enterprise data asset management method and system based on block chain Technical Field The invention relates to the technical field of data processing, in particular to an enterprise data asset management method and system based on a blockchain. Background Blockchains are a distributed ledger technique that records data in a decentralised manner, ensuring the security, transparency and non-tamper ability of the data. The core goals of enterprise data asset management are to ensure data security, transparency, and efficiency, among others. Managing data assets of an enterprise based on blockchains thus enables the enterprise to increase the trustworthiness, security, and efficiency of data during data management. With the development of technology, side chain technology has been developed to facilitate the transfer of digital assets from one blockchain to another. Which interconnects different blockchains together to achieve expansion of the blockchain. For enterprise-level data assets, a large amount of transaction data and log data can be involved, but the private chain (main chain) has limited scale and real-time throughput, and the cost of directly expanding the main chain is high, so that a better enterprise side chain expansion strategy is formulated, and an automatic and intelligent data management solution can be provided for enterprises. However, the existing method adopts a fixed side chain expansion strategy, which has poor effect on enterprise-level data asset management. Disclosure of Invention In order to solve the technical problem that the prior method adopts a fixed side chain expansion strategy and has poor effect on enterprise-level data asset management, the invention aims to provide a block chain-based enterprise data asset management method and system, and the adopted technical scheme is as follows: in a first aspect, the present invention provides a blockchain-based enterprise data asset management method, comprising: Acquiring each business module with enterprise asset data stored in each side chain; Combining the side chains according to the interaction information between each service module in each side chain and each service module in other side chains and combining the core difference condition among data contained in different service modules, and determining an initial storage strategy of a block chain structure; Under the initial storage strategy, according to the memory use condition and bandwidth information of each side chain at each updating moment, the load change condition of the corresponding side chain is analyzed, the synchronization degree of each side chain at each updating moment is adjusted in real time by combining the updating condition of the side chain at the historical updating moment, and the global storage strategy of the block chain structure is determined. Preferably, the acquiring each business module of the enterprise asset data stored in each side chain specifically includes: acquiring confidentiality marking value, access frequency and update frequency of each type of enterprise data in the enterprise asset data; Obtaining the core index of each type of enterprise data according to the confidentiality marking value of each type of enterprise data, the access frequency and the update frequency of all enterprise data of the same type; Dividing the enterprise data with different core grades according to the different change conditions of the core index among the enterprise data with different types; Enterprise data belonging to the same service and the same core class are used as the same service module, different types of enterprise data contained in each service module are stored in side chains, and one side chain at least comprises one service module. Preferably, the obtaining the core degree index of each type of enterprise data according to the confidentiality degree flag value of each type of enterprise data, the access frequency and the update frequency of all enterprise data of the same type specifically includes: determining a first importance coefficient corresponding to each type of enterprise data based on the confidentiality marking value of each type of enterprise data and the average value of the access frequencies of all enterprise data of the same type; Determining a second important coefficient corresponding to each type of enterprise data based on a difference between a maximum value of update frequencies of all types of enterprise data and a mean value of update frequencies of all types of enterprise data; and obtaining the core index of each type of enterprise data according to the first important coefficient and the second important coefficient. Preferably, the dividing the enterprise data with different core levels according to the variation condition of the core index between the enterprise data with different types specifically includes: the core indexes of all types of enterprise data are arranged according to a preset sequence