Block chain evidence storage method and system for cultural big data content security supervision and medium

Abstract

The invention provides a block chain evidence storage method and system for cultural big data content security supervision and a medium. The method comprises the following steps: obtaining an intentional evidence storage center after obtaining an evidence storage system architecture of culture big data and a hierarchical evidence storage level of intentional evidence storage culture big data, preprocessing the intentional evidence storage culture big data to obtain category feature data and content security feature data, and calculating to obtain a hash value through a hash function, combining with the content security feature data to generate evidence storage summary data, uploading the evidence storage summary data to a block chain network, and completing uplink evidence storage to obtain evidence storage culture big data; therefore, block chain evidence storage of cultural big data content security supervision is realized through distinguishing the cultural big data evidence storage center and generating the hash value and evidence storage abstract data.

Description

Technical Field

[0001] The present application relates to the field of content security supervision of cultural big data. Specifically, it relates to a blockchain evidence storage method, system and medium for content security supervision of cultural big data. Background Art

[0002] With the rapid development of the cultural big data industry, the scale and value of cultural data have been continuously increasing. The national cultural big data system covers multiple links such as the supply side, production side, cloud side and demand side, and data flows and is processed in these links. However, at present, the content security of cultural big data faces many challenges. During the process of data transmission and storage, the risk of data tampering is high. Once the data is maliciously tampered with, it will affect the authenticity and reliability of cultural data. For example, if cultural heritage data, cultural gene data, etc. are tampered with, it will damage the accuracy of cultural inheritance.

[0003] The existing content security supervision technologies are difficult to achieve effective supervision over the entire life cycle of data. Traditional encryption and authentication technologies have supervision loopholes when facing complex network environments and scenarios involving multiple parties. At the same time, there are also problems with the copyright protection of data. The property rights of cultural data are complex and the requirements for copyright protection are high. Existing technologies are difficult to ensure the clear copyright attribution of cultural data assets, resulting in easy occurrence of copyright disputes during the cultural data transaction process, which affects the healthy development of the cultural industry. Therefore, there is an urgent need for an innovative method to solve the problem of content security supervision of cultural big data. Summary of the Invention

[0004] The purpose of the present application is to provide a blockchain evidence storage method, system and medium for content security supervision of cultural big data, which can realize the blockchain evidence storage of content security supervision of cultural big data by differentiating the cultural big data evidence storage center, generating hash values and evidence storage summary data.

[0005] The present application also provides a blockchain evidence storage method for content security supervision of cultural big data, including the following steps: Obtain the evidence storage system architecture of cultural big data and the hierarchical evidence storage level of the intended evidence storage cultural big data. After performing hierarchical evidence storage matching, obtain the intended evidence storage center; Preprocess the intended evidence storage cultural big data to obtain category feature data and content security feature data; Calculate the corresponding hash value by passing the category feature data and the intended evidence storage cultural big data through a preset hash function, and generate evidence storage summary data in combination with the content security feature data; Upload the constructed evidence storage summary data to the blockchain network through a preset smart contract and complete the on-chain evidence storage to obtain the evidence storage cultural big data.

[0006] Optionally, in the blockchain-based evidence preservation method for cultural big data content security supervision described in this application, after obtaining the evidence preservation system architecture of cultural big data and the hierarchical evidence preservation levels of the intended evidence-preserved cultural big data, and performing hierarchical evidence preservation matching, obtaining the intended evidence preservation center specifically includes: Obtain the evidence preservation system architecture of cultural big data, including the national center, regional center, and provincial center; Obtain the hierarchical evidence preservation levels of the intended evidence-preserved cultural big data, including high-level evidence preservation, medium-level evidence preservation, or primary evidence preservation; Match the hierarchical evidence preservation levels with the evidence preservation system architecture according to preset rules to obtain the intended evidence preservation center of the intended evidence-preserved cultural big data.

[0007] Optionally, in the blockchain-based evidence preservation method for cultural big data content security supervision described in this application, after preprocessing the intended evidence-preserved cultural big data to obtain category feature data and content security feature data, specifically includes: Extract features from the intended evidence-preserved cultural big data to obtain category feature data and original content security feature data. The category feature data includes text category data, picture category data, audio category data, or video category data; Encrypt the original content security feature data through a preset quantum encryption technology to obtain content security feature data, including content fingerprint feature data, metadata, and semantic feature data; Among them, the content fingerprint feature data includes data collection time, collector, and copyright information, and the metadata includes creator, creation time, and theme data.

[0008] Optionally, in the blockchain-based evidence preservation method for cultural big data content security supervision described in this application, calculating the corresponding hash value by passing the category feature data and the intended evidence-preserved cultural big data through a preset hash function, and generating evidence preservation summary data in combination with the content security feature data, specifically includes: Calculate the hash value of the category feature data and the intended evidence-preserved cultural big data through multiple preset hash algorithms respectively, and generate a composite hash value after fusing the hash values; Combine the composite hash value with the content fingerprint feature data, metadata, and semantic feature data to generate evidence preservation summary data.

[0009] Optionally, in the blockchain-based evidence preservation method for cultural big data content security supervision described in this application, uploading the constructed evidence preservation summary data to the blockchain network through a preset smart contract and completing the on-chain evidence preservation to obtain evidence-preserved cultural big data, specifically includes: Write the evidence preservation summary data into the blockchain ledger through a preset smart contract to generate an evidence preservation block; The evidence storage block is broadcast to blockchain nodes through a blockchain network, and the blockchain nodes conduct consensus through a preset proof of work to obtain the validity and reliability of the evidence storage summary data; If the validity and reliability pass the verification, the evidence storage summary data completes the on-chain evidence storage to obtain the evidence storage cultural big data.

[0010] Optionally, in the blockchain evidence storage method for cultural big data content security supervision described in this application, after obtaining the composite hash value, it further includes: Obtain the importance level of the cultural big data, including very important, generally important, or unimportant; Obtain the corresponding dynamic hash calculation period and dynamic hash calculation start degree threshold according to the importance level; Obtain the content update degree data and the duration data since the last update of the cultural big data; Compare the content update degree data with the dynamic hash calculation start degree threshold to obtain the content update status data; Compare the duration data with the dynamic hash calculation period to obtain the period update status data; Perform an OR operation on the content update status data and the period update status data to obtain the hash value update requirement data, including the need to update or not to update; Determine the execution status of the hash algorithm according to the hash value update requirement data.

[0011] Optionally, in the blockchain evidence storage method for cultural big data content security supervision described in this application, it further includes: Obtain the address data and environmental condition data of the access network. The address data includes common address data or uncommon address data, and the environmental condition data includes safe environment data or risk environment data; Calculate the authentication evaluation data according to the address data and the environmental condition data; Query the preset security authentication dynamic adjustment rules according to the authentication evaluation data to obtain the corresponding dynamic identity authentication strategy.

[0012] In a second aspect, this application provides a blockchain evidence storage system for cultural big data content security supervision. The system includes: a memory and a processor. The memory includes a program for the blockchain evidence storage method for cultural big data content security supervision. When the program for the blockchain evidence storage method for cultural big data content security supervision is executed by the processor, the following steps are implemented: Obtain the evidence storage architecture of the cultural big data and the hierarchical evidence storage level of the intended evidence storage cultural big data. After performing hierarchical evidence storage matching, obtain the intended evidence storage center; Preprocess the intended evidence storage cultural big data to obtain category feature data and content security feature data; Calculate the corresponding hash value for the category feature data and the intended archived cultural big data through a preset hash function, and generate archived summary data in combination with the content security feature data; Upload the constructed archived summary data to the blockchain network through a preset smart contract and complete the on-chain archiving to obtain the archived cultural big data.

[0013] Optionally, in the blockchain archiving system for the content security supervision of the cultural big data described in this application, after obtaining the archiving system architecture of the cultural big data and the hierarchical archiving levels of the intended archived cultural big data, and performing hierarchical archiving matching, an intended archived center is obtained, which specifically includes: Obtain the archiving system architecture of the cultural big data, including the national center, regional center, and provincial center; Obtain the hierarchical archiving levels of the intended archived cultural big data, including high-level archiving, medium-level archiving, or primary archiving; Match the hierarchical archiving levels with the archiving system architecture according to preset rules to obtain the intended archived center of the intended archived cultural big data.

[0014] In a third aspect, this application also provides a readable storage medium, in which a program for the blockchain archiving method for the content security supervision of cultural big data is stored. When the program for the blockchain archiving method for the content security supervision of cultural big data is executed by a processor, the steps of a blockchain archiving method for the content security supervision of cultural big data as described in any one of the above are implemented.

[0015] As can be seen from the above, this application provides a blockchain archiving method, system, and medium for the content security supervision of cultural big data. After obtaining the archiving system architecture of the cultural big data and the hierarchical archiving levels of the intended archived cultural big data, the method obtains the intended archived center. After preprocessing the intended archived cultural big data to obtain category feature data and content security feature data, it calculates the hash value through a hash function, and then combines it with the content security feature data to generate archived summary data. The archived summary data is uploaded to the blockchain network and the on-chain archiving is completed to obtain the archived cultural big data; thereby, through the differentiation of the cultural big data archiving center and the generation of the hash value and the archived summary data, the blockchain archiving of the content security supervision of cultural big data is realized.

[0016] Other features and advantages of this application will be described in the subsequent specification, and part of them will become obvious from the specification, or can be understood by implementing this application. The purpose and other advantages of this application can be achieved and obtained through the structures specifically pointed out in the written specification and the drawings. Description of the Drawings

[0017] To more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required for use in the embodiments of the present application. It should be understood that the following drawings only show certain embodiments of the present application and should not be regarded as limiting the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0018] Figure 1 It is a flowchart of a blockchain deposit and evidence method for cultural big data content security supervision provided by an embodiment of the present application; Figure 2 It is a flowchart of obtaining an intended deposit and evidence center for a blockchain deposit and evidence method for cultural big data content security supervision provided by an embodiment of the present application; Figure 3 It is a flowchart of generating deposit and evidence summary data for a blockchain deposit and evidence method for cultural big data content security supervision provided by an embodiment of the present application. Specific embodiments

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, rather than all embodiments. Usually, the components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the present application to be protected, but only represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0020] It should be noted that: similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present application, terms such as "first" and "second" are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0021] Please refer to Figure 1 , Figure 1 is a flowchart of a blockchain deposit and evidence method for cultural big data content security supervision in some embodiments of the present application. This blockchain deposit and evidence method for cultural big data content security supervision is used in terminal devices, such as computers, mobile phones, etc. This blockchain deposit and evidence method for cultural big data content security supervision includes the following steps: S11. Obtain the deposit and evidence system architecture of cultural big data and the hierarchical deposit and evidence levels of the intended deposit and evidence cultural big data. After performing hierarchical deposit and evidence matching, obtain the intended deposit and evidence center; S12. Preprocess the intended archived cultural big data to obtain category feature data and content security feature data; S13. Calculate the corresponding hash values for the category feature data and the intended archived cultural big data through a preset hash function, and generate archived summary data by combining the content security feature data; S14. Upload the constructed archived summary data to the blockchain network through a preset smart contract and complete the on-chain archiving to obtain archived cultural big data.

[0022] It should be noted that the national cultural big data system has a three-level architecture, namely the national center, regional centers, and provincial centers. Corresponding blockchain nodes will be deployed in the three-level architecture to form a consortium chain network; the national center serves as the root node, the regional centers serve as intermediate nodes, the provincial centers serve as leaf nodes, and cultural institutions access as clients; different cultural big data have different hierarchical archiving requirements, which is conducive to improving efficiency. Therefore, after obtaining the hierarchical archiving level of the intended archived cultural big data, perform hierarchical archiving matching to obtain the intended archived center; preprocess the intended archived cultural big data to obtain category feature data and content security feature data. The acquisition of category feature data can distinguish the intended archived cultural big data, which is convenient for storage and query. Calculate the hash value based on the category feature data and the intended archived cultural big data, combine the hash value with the content security feature data to generate archived summary data, and finally upload the constructed archived summary data to the blockchain network through a preset smart contract for on-chain archiving.

[0023] Please refer to Figure 2 , Figure 2 is a flowchart of obtaining the intended archived center of a blockchain archiving method for content security supervision of cultural big data provided by an embodiment of the present application. According to an embodiment of the present invention, after obtaining the archiving system architecture of cultural big data and the hierarchical archiving level of the intended archived cultural big data, perform hierarchical archiving matching to obtain the intended archived center, which specifically includes: S21. Obtain the archiving system architecture of cultural big data, including the national center, regional centers, and provincial centers; S22. Obtain the hierarchical archiving level of the intended archived cultural big data, including high-level archiving, medium-level archiving, or low-level archiving; S23. Match the hierarchical archiving level with the archiving system architecture according to a preset rule to obtain the intended archived center of the intended archived cultural big data.

[0024] It should be noted that the intended archived cultural big data refers to the cultural big data that needs to be archived on the blockchain for content security supervision; the hierarchical archiving mechanism is the core design of the national cultural big data blockchain system. By dividing the archiving process into three levels: primary, intermediate, and advanced, it realizes efficient, secure, and scalable supervision of cultural digital content. In primary archiving, cultural institutions submit the content feature hash value to the provincial center blockchain node; in intermediate archiving, the regional center node aggregates and verifies multiple provincial archivings; in advanced archiving, the national center node finally confirms and archives the full-chain archived data; the hierarchical archiving level of the intended archived cultural big data is matched with the archiving system architecture according to preset rules, and the matching rules are as follows:

[0025] After matching, the intended archived center is obtained.

[0026] According to an embodiment of the present invention, the preprocessing of the intended archived cultural big data to obtain category feature data and content security feature data specifically includes: Feature extraction is performed on the intended archived cultural big data to obtain category feature data and original content security feature data. The category feature data includes text category data, picture category data, audio category data, or video category data; The original content security feature data is encrypted through a preset quantum encryption technology to obtain content security feature data, including content fingerprint feature data, metadata, and semantic feature data; Among them, the content fingerprint feature data includes data collection time, collector, and copyright information, and the metadata includes creator, creation time, and theme data.

[0027] It should be noted that the original content security feature data refers to the data closely related to the cultural big data determined according to the content of the cultural big data; the quantum encryption technology is based on the principles of non-clonability and uncertainty of quantum states, and can provide an encryption method that is theoretically absolutely secure, preventing data from being stolen and cracked during the preprocessing stage and subsequent transmission and storage processes; the original content security feature data is encrypted through the quantum encryption technology to obtain the content security feature data.

[0028] Please refer to Figure 3 , Figure 3 is a flowchart for generating archived summary data of a blockchain archiving method for cultural big data content security supervision provided by an embodiment of the present application. According to an embodiment of the present invention, the corresponding hash value is calculated by using the category feature data and the intended archived cultural big data through a preset hash function, and the archived summary data is generated in combination with the content security feature data, specifically including: S31. Calculate the hash values of the category feature data and the intended archived cultural big data respectively through multiple preset hash algorithms, and generate a composite hash value after fusing the hash values; S32. Combine the composite hash value with the content fingerprint feature data, metadata, and semantic feature data to generate archived summary data.

[0029] It should be noted that after combining the category feature data with the intended archived cultural big data, the archived data can be quickly classified. The hash algorithms can be SHA-256, Keccak-256, etc. When calculating using the hash algorithm, the obtained hash value is unique and irreversible; the archived summary refers to the streamlined feature information generated by processing the original data through specific technical means during the data archiving process. Its core function is to significantly reduce the cost of data storage and transmission while ensuring data integrity and verifiability, and to ensure the traceability of the authenticity of the original data; there are multiple methods to fuse the hash values, including re-hashing after concatenation, XOR operation fusion, or weighted sum fusion. The specific method can be selected according to user needs.

[0030] According to the embodiment of the present invention, uploading the constructed archived summary data to the blockchain network through a preset smart contract and completing the on-chain archiving to obtain archived cultural big data specifically includes: Write the archived summary data into the blockchain ledger through a preset smart contract to generate an archived block; The archived block is broadcast to the blockchain nodes through the blockchain network, and the blockchain nodes perform consensus through a preset proof of work to obtain the validity and reliability of the archived summary data; If the validity and reliability pass the verification, the archived summary data completes the on-chain archiving to obtain archived cultural big data.

[0031] It should be noted that a smart contract is an automatically executed contract clause deployed on the blockchain in the form of code. In the content security supervision of cultural big data, smart contracts can be used to define the rules and processes of archiving, such as stipulating that only authorized users can perform data archiving, or automatically triggering archiving operations under specific conditions, etc.; the proof of work is a blockchain consensus mechanism that verifies transactions and generates new blocks by calculating complex mathematical problems; if the validity and reliability do not pass the verification, an unqualified warning is issued.

[0032] According to the embodiment of the present invention, after obtaining the composite hash value, it further includes: Obtain the importance level of the cultural big data, including very important, generally important, or unimportant; Obtain the corresponding dynamic hash calculation period and dynamic hash calculation start degree threshold according to the importance level; Obtain the content update degree data and the duration data since the last update of the cultural big data; Compare the content update degree data with the dynamic hash calculation start degree threshold to obtain the content update status data; Compare the duration data with the dynamic hash calculation period to obtain the periodic update status data; Perform an OR operation on the content update status data and the periodic update status data to obtain the hash value update requirement data, including whether to update or not to update; Determine the execution status of the hash algorithm according to the hash value update requirement data.

[0033] It should be noted that cultural big data often has different importance levels and different update requirements. The dynamic hash calculation period means that cultural big data implements dynamic evidence storage management, and the hash calculation period can be set according to user needs. This period can be 1 day or 1 week; the dynamic hash calculation start degree threshold refers to the cultural big data that implements dynamic evidence storage management. When the update degree reaches the preset threshold, the dynamic evidence storage management process is started; the calculation of the content update degree data can be calculated according to the proportion of the updated content part in the overall content. The content update status data includes that the content update reaches the dynamic update status data and the content update does not reach the dynamic update status data, which are represented by 1 and 0 respectively; the periodic update status data includes reaching the periodic update status and not reaching the periodic update status, which are represented by 1 and 0 respectively; when one of the content update status data and the periodic update status data meets the requirements, the dynamic evidence storage management process is started.

[0034] According to an embodiment of the present invention, it further includes: Obtain the address data and environmental condition data for accessing the network. The address data includes common address data or uncommon address data, and the environmental condition data includes secure environment data or risk environment data; Calculate the authentication evaluation data according to the address data and the environmental condition data; Query the preset security authentication dynamic adjustment rules according to the authentication evaluation data to obtain the corresponding dynamic identity authentication strategy.

[0035] It should be noted that when a user accesses, in order to ensure data security, it is necessary to judge according to the address data and environmental condition data for accessing the network; the specific method is to define the address data and environmental condition data respectively. The common address data and uncommon address data are defined as 1 and 0 respectively; the secure environment data and risk environment data are defined as 1 and 0 respectively; add the address data and environmental condition data to obtain the authentication evaluation data; the preset security authentication dynamic adjustment rules are:

[0036] Faces, fingerprints, and irises are biometric features collected in advance for users, and specific biometric features can be freely selected according to user needs.

[0037] The present invention also discloses a blockchain evidence storage system for cultural big data content security supervision, including a memory and a processor. A program for the blockchain evidence storage method for cultural big data content security supervision is stored in the memory. When the program for the blockchain evidence storage method for cultural big data content security supervision is executed by the processor, the following steps are implemented: Obtain the evidence storage system architecture of cultural big data and the hierarchical evidence storage level of the intended evidence storage cultural big data. After performing hierarchical evidence storage matching, obtain the intended evidence storage center; Preprocess the intended evidence storage cultural big data to obtain category feature data and content security feature data; Calculate the corresponding hash value for the category feature data and the intended evidence storage cultural big data through a preset hash function, and generate evidence storage summary data in combination with the content security feature data; Upload the constructed evidence storage summary data to the blockchain network through a preset smart contract and complete on-chain evidence storage to obtain the evidence storage cultural big data.

[0038] It should be noted that the national cultural big data system has a three-level architecture, namely the national center, regional centers, and provincial centers. Corresponding blockchain nodes will be deployed in the three-level architecture to form a consortium chain network; the national center serves as the root node, the regional centers serve as intermediate nodes, the provincial centers serve as leaf nodes, and cultural institutions access as clients; different cultural big data have different hierarchical evidence storage requirements, which is conducive to improving efficiency. Therefore, after obtaining the hierarchical evidence storage level of the intended evidence storage cultural big data, perform hierarchical evidence storage matching to obtain the intended evidence storage center; preprocess the intended evidence storage cultural big data to obtain category feature data and content security feature data. The acquisition of category feature data can distinguish the intended evidence storage cultural big data, which is convenient for storage and query. Calculate the hash value based on the category feature data and the intended evidence storage cultural big data, combine the hash value with the content security feature data to generate evidence storage summary data, and finally upload the constructed evidence storage summary data to the blockchain network through a preset smart contract for on-chain evidence storage.

[0039] According to an embodiment of the present invention, the step of obtaining the evidence storage system architecture of cultural big data and the hierarchical evidence storage level of the intended evidence storage cultural big data, and obtaining the intended evidence storage center after performing hierarchical evidence storage matching specifically includes: Obtain the evidence storage system architecture of cultural big data, including the national center, regional centers, and provincial centers; Obtain the hierarchical evidence storage level of the intended evidence storage cultural big data, including high-level evidence storage, medium-level evidence storage, or low-level evidence storage; Match the hierarchical deposit and certification levels with the deposit and certification system architecture according to preset rules to obtain the intended deposit and certification center for the intended cultural big data of deposit and certification.

[0040] It should be noted that the intended cultural big data of deposit and certification refers to the cultural big data that needs to be stored and certified on the blockchain for content security supervision; the hierarchical deposit and certification mechanism is the core design of the national cultural big data blockchain system. By dividing the deposit and certification process into three levels: primary, intermediate, and advanced, it realizes efficient, secure, and scalable supervision of cultural digital content. In primary deposit and certification, cultural institutions submit the content feature hash value to the provincial center blockchain node; in intermediate deposit and certification, the regional center node aggregates and verifies multiple provincial deposits and certifications; in advanced deposit and certification, the national center node finally confirms and archives the deposit and certification data of the entire chain. Match the hierarchical deposit and certification levels of the intended cultural big data of deposit and certification with the deposit and certification system architecture according to preset rules. The matching rules are as follows:

[0041] After matching, obtain the intended deposit and certification center.

[0042] According to an embodiment of the present invention, the preprocessing of the intended cultural big data of deposit and certification to obtain category feature data and content security feature data specifically includes: Extract features from the intended cultural big data of deposit and certification to obtain category feature data and original content security feature data. The category feature data includes text category data, picture category data, audio category data, or video category data; Encrypt the original content security feature data through a preset quantum encryption technology to obtain content security feature data, including content fingerprint feature data, metadata, and semantic feature data; Among them, the content fingerprint feature data includes data collection time, collector, and copyright information, and the metadata includes creator, creation time, and theme data.

[0043] It should be noted that the original content security feature data refers to the data closely related to the cultural big data determined according to the content of the cultural big data; the quantum encryption technology is based on the principles of the non-clonability and uncertainty of quantum states, and can provide an encryption method that is theoretically absolutely secure, preventing data from being stolen and cracked during the preprocessing stage and subsequent transmission and storage processes. The original content security feature data is encrypted through the quantum encryption technology to obtain the content security feature data.

[0044] According to an embodiment of the present invention, the calculation of the corresponding hash value by using the category feature data and the intended cultural big data of deposit and certification through a preset hash function, and generating the deposit and certification summary data in combination with the content security feature data specifically includes: Calculate the hash values of the category feature data and the intended archived cultural big data respectively through a variety of preset hash algorithms, and generate a composite hash value after fusing the hash values; Combine the composite hash value with the content fingerprint feature data, metadata, and semantic feature data to generate archived summary data.

[0045] It should be noted that after combining the category feature data with the intended archived cultural big data, the archived data can be quickly classified. The hash algorithms can be SHA-256, Keccak-256, etc. When calculating using the hash algorithm, the calculated hash value has uniqueness and irreversibility; the archived summary refers to the streamlined feature information generated by processing the original data through specific technical means during the data archiving process. Its core function is to significantly reduce the cost of data storage and transmission while ensuring data integrity and verifiability, and to ensure the traceability of the authenticity of the original data; there are multiple methods to fuse the hash values, including re-hashing after concatenation, XOR operation fusion, or weighted sum fusion. The specific method can be selected according to user needs.

[0046] According to an embodiment of the present invention, uploading the constructed archived summary data to the blockchain network through a preset smart contract and completing the on-chain archiving to obtain archived cultural big data specifically includes: Write the archived summary data into the blockchain ledger through a preset smart contract to generate an archived block; The archived block is broadcast to the blockchain nodes through the blockchain network, and the blockchain nodes perform consensus through a preset proof of work to obtain the validity and reliability of the archived summary data; If the validity and reliability pass the verification, the archived summary data completes the on-chain archiving to obtain archived cultural big data.

[0047] It should be noted that a smart contract is an automatically executed contract clause deployed on the blockchain in the form of code. In the content security supervision of cultural big data, smart contracts can be used to define the rules and processes of archiving, such as stipulating that only authorized users can perform data archiving, or automatically triggering archiving operations under specific conditions, etc.; the proof of work is a blockchain consensus mechanism that verifies transactions and generates new blocks by calculating complex mathematical problems; if the validity and reliability do not pass the verification, an unqualified warning is issued.

[0048] According to an embodiment of the present invention, after obtaining the composite hash value, it further includes: Obtain the importance level of the cultural big data, including very important, generally important, or unimportant; Obtain the corresponding dynamic hash calculation period and dynamic hash calculation start degree threshold according to the importance level; Obtain the content update degree data and the duration data since the last update of the cultural big data; Compare the content update degree data with the dynamic hash calculation start degree threshold to obtain the content update status data; Compare the duration data with the dynamic hash calculation period to obtain the period update status data; Perform an OR operation on the content update status data and the period update status data to obtain the hash value update requirement data, including whether to update or not; Determine the execution status of the hash algorithm according to the hash value update requirement data.

[0049] It should be noted that cultural big data often has different levels of importance and different update requirements. The dynamic hash calculation period means that cultural big data implements dynamic evidence preservation management, and the hash calculation period can be set according to user needs. This period can be 1 day or 1 week. The dynamic hash calculation start degree threshold refers to the cultural big data that implements dynamic evidence preservation management. When the update degree reaches the preset threshold, the dynamic evidence preservation management process is started. The calculation of the content update degree data can be based on the proportion of the updated content part in the overall content. The content update status data includes that the content update reaches the dynamic update status data and the content update does not reach the dynamic update status data, which are represented by 1 and 0 respectively. The period update status data includes reaching the period update status and not reaching the period update status, which are represented by 1 and 0 respectively. When one of the content update status data and the period update status data meets the requirements, the dynamic evidence preservation management process is started.

[0050] According to an embodiment of the present invention, it further includes: Obtain the address data and environmental condition data for accessing the network. The address data includes common address data or uncommon address data, and the environmental condition data includes safe environment data or risk environment data; Calculate the authentication evaluation data according to the address data and the environmental condition data; Query the preset security authentication dynamic adjustment rules according to the authentication evaluation data to obtain the corresponding dynamic identity authentication strategy.

[0051] It should be noted that when a user accesses, in order to ensure data security, it is necessary to judge according to the address data and environmental condition data for accessing the network. The specific method is to define the address data and environmental condition data respectively. The common address data and uncommon address data are defined as 1 and 0 respectively; the safe environment data and risk environment data are defined as 1 and 0 respectively; add the address data and environmental condition data to obtain the authentication evaluation data. The preset security authentication dynamic adjustment rules are:

[0052] Faces, fingerprints, and irises are biometric features collected in advance for users. Specific biometric features can be freely selected according to user needs.

[0053] In a third aspect of the present invention, a readable storage medium is provided. The readable storage medium includes a program for a blockchain evidence storage method for cultural big data content security supervision. When the program for the blockchain evidence storage method for cultural big data content security supervision is executed by a processor, the steps of a blockchain evidence storage method for cultural big data content security supervision as described in any one of the above are implemented.

[0054] A blockchain evidence storage method, system, and medium for cultural big data content security supervision disclosed in the present invention obtain an intended evidence storage center by acquiring the evidence storage system architecture of cultural big data and the hierarchical evidence storage level of the intended evidence storage cultural big data. After preprocessing the intended evidence storage cultural big data to obtain category feature data and content security feature data, a hash value is calculated through a hash function, and then combined with the content security feature data to generate evidence storage summary data. The evidence storage summary data is uploaded to the blockchain network and the on-chain evidence storage is completed to obtain the evidence storage cultural big data; thereby, through the differentiation of the cultural big data evidence storage center and the generation of the hash value and the evidence storage summary data, the blockchain evidence storage of cultural big data content security supervision is realized.

[0055] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored, or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed with each other can be through some interfaces. The indirect coupling or communication connection of the devices or units can be electrical, mechanical, or other forms.

[0056] The units described above as separate components may or may not be physically separated. The components shown as units may or may not be physical units; they can be located in one place or distributed to multiple network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0057] In addition, in each embodiment of the present invention, the various functional units can all be integrated in one processing unit, or each unit can be separately used as one unit, or two or more units can be integrated in one unit; the above integrated units can be implemented in the form of hardware, or in the form of a combination of hardware and software functional units.

[0058] Those of ordinary skill in the art can understand that all or part of the steps to implement the above method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a readable storage medium. When the program is executed, it performs the steps including those of the above method embodiments. The aforementioned storage medium includes various media that can store program codes, such as removable storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs.

[0059] Alternatively, if the above integrated unit of the present invention is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a readable storage medium. Based on such an understanding, the technical solution of the embodiments of the present invention, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. The software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media that can store program codes, such as removable storage devices, ROM, RAM, magnetic disks, or optical discs.

Claims

1. A blockchain deposit and proof method for content security supervision of cultural big data, characterized in that, Including: Obtain the archival evidence system architecture of cultural big data and the hierarchical archival evidence levels of the intended archival evidence cultural big data. After performing hierarchical archival evidence matching, obtain the intended archival evidence center; Preprocess the intended archival evidence cultural big data to obtain category feature data and content security feature data; Calculate the corresponding hash values for the category feature data and the intended archival evidence cultural big data through a preset hash function, and generate archival evidence summary data in combination with the content security feature data; Upload the constructed archival evidence summary data to the blockchain network through a preset smart contract and complete the on-chain archival evidence to obtain archival evidence cultural big data.

2. The blockchain deposit and proof method for cultural big data content security supervision according to claim 1, wherein, The obtaining of the archival evidence system architecture of cultural big data and the hierarchical archival evidence levels of the intended archival evidence cultural big data, and after performing hierarchical archival evidence matching to obtain the intended archival evidence center specifically includes: Obtain the archival evidence system architecture of cultural big data, including the national center, regional center, and provincial center; Obtain the hierarchical archival evidence levels of the intended archival evidence cultural big data, including high-level archival evidence, medium-level archival evidence, or low-level archival evidence; Match the hierarchical archival evidence levels with the archival evidence system architecture according to preset rules to obtain the intended archival evidence center of the intended archival evidence cultural big data.

3. The blockchain deposit and certification method for cultural big data content security supervision according to claim 2, wherein The preprocessing of the intended archival evidence cultural big data to obtain category feature data and content security feature data specifically includes: Extract features from the intended archival evidence cultural big data to obtain category feature data and original content security feature data. The category feature data includes text category data, picture category data, audio category data, or video category data; Encrypt the original content security feature data through a preset quantum encryption technology to obtain content security feature data, including content fingerprint feature data, metadata, and semantic feature data; Among them, the content fingerprint feature data includes data collection time, collector, and copyright information, and the metadata includes creator, creation time, and theme data.

4. The blockchain evidence storage method for cultural big data content security supervision according to claim 3, characterized in that, The calculating of the corresponding hash values for the category feature data and the intended archival evidence cultural big data through a preset hash function and generating archival evidence summary data in combination with the content security feature data specifically includes: Calculate the hash values for the category feature data and the intended archival evidence cultural big data through multiple preset hash algorithms respectively, and generate a composite hash value after fusing the hash values; Combine the composite hash value with the content fingerprint feature data, metadata, and semantic feature data to generate archival evidence summary data.

5. The blockchain evidence storage method for the cultural big data content security supervision according to claim 4, characterized in that, The uploading of the constructed archival evidence summary data to the blockchain network through a preset smart contract and completing the on-chain archival evidence to obtain archival evidence cultural big data specifically includes: Write the archival evidence summary data into the blockchain ledger through a preset smart contract to generate an archival evidence block; The archival evidence block is broadcast to the blockchain nodes through the blockchain network, and the blockchain nodes perform consensus through a preset proof-of-work to obtain the validity and reliability of the archival evidence summary data; If the validity and reliability pass the verification, the archival evidence summary data completes the on-chain archival evidence to obtain archival evidence cultural big data.

6. The blockchain deposit and certification method for cultural big data content security supervision according to claim 5, wherein After obtaining the composite hash value, it further includes: Obtain the importance level of the cultural big data, including very important, generally important, or unimportant; Obtain the corresponding dynamic hash calculation period and dynamic hash calculation start degree threshold according to the importance level; Obtain the content update degree data and the duration data since the last update of the cultural big data; Compare the content update degree data with the dynamic hash calculation start degree threshold to obtain the content update status data; Compare the duration data with the dynamic hash calculation period to obtain the period update status data; Perform an OR operation on the content update status data and the period update status data to obtain the hash value update requirement data, including whether to update or not to update; Determine the hash algorithm execution status according to the hash value update requirement data.

7. The blockchain evidence storage method for cultural big data content security supervision according to claim 6, characterized in that, It further includes: Obtain the address data and environmental condition data for accessing the network. The address data includes common address data or uncommon address data, and the environmental condition data includes secure environment data or risk environment data; Calculate the authentication evaluation data according to the address data and environmental condition data; Query the preset security authentication dynamic adjustment rules according to the authentication evaluation data to obtain the corresponding dynamic identity authentication policy.

8. A blockchain evidence storage system for content security supervision of cultural big data, characterized in that, It includes a memory and a processor. The memory includes a blockchain deposit and proof method program for cultural big data content security supervision. When the blockchain deposit and proof method program for cultural big data content security supervision is executed by the processor, the following steps are implemented: Obtain the deposit and proof system architecture of the cultural big data and the hierarchical deposit and proof level of the intended deposit and proof cultural big data. After performing hierarchical deposit and proof matching, obtain the intended deposit and proof center; Preprocess the intended deposit and proof cultural big data to obtain category feature data and content security feature data; Calculate the corresponding hash value for the category feature data and the intended deposit and proof cultural big data through a preset hash function, and generate deposit and proof summary data in combination with the content security feature data; Upload the constructed deposit and proof summary data to the blockchain network through a preset smart contract and complete the on-chain deposit and proof to obtain the deposit and proof cultural big data.

9. The blockchain evidence storage system for cultural big data content security supervision according to claim 8, characterized in that, The step of obtaining the deposit and proof system architecture of the cultural big data and the hierarchical deposit and proof level of the intended deposit and proof cultural big data, and obtaining the intended deposit and proof center after performing hierarchical deposit and proof matching specifically includes: Obtain the deposit and proof system architecture of the cultural big data, including the national center, regional center, and provincial center; Obtain the hierarchical deposit and proof level of the intended deposit and proof cultural big data, including high-level deposit and proof, medium-level deposit and proof, or primary-level deposit and proof; Match the hierarchical deposit and proof level with the deposit and proof system architecture according to preset rules to obtain the intended deposit and proof center of the intended deposit and proof cultural big data.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a blockchain deposit and proof method program for cultural big data content security supervision. When the blockchain deposit and proof method program for cultural big data content security supervision is executed by the processor, the steps of the blockchain deposit and proof method for cultural big data content security supervision described in any one of claims 1 to 7 are implemented.

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