Cross-domain data compliance mutual trust calculation method

Abstract

The invention relates to the field of calculation methods, in particular to a cross-domain data compliance mutual trust calculation method, which comprises the following steps: S1, cross-domain data access control based on a block chain; s2, cross-domain organization key uplink; s3, cross-domain data compliance distinguishing; s4, constructing a cross-domain data exchange model; s5, cross-domain data are linked by using a block chain; s6, performing homomorphic operation on cross-domain data; s7, the homomorphic operation result is linked; and S8, obtaining a homomorphic operation result. According to the method, on the premise of protection requirements of laws and regulations of two places on related data, a cross-domain data compliance mutual trust calculation method is constructed to realize cross-regional data processing. An alliance block chain is utilized to construct a cross-domain organization mutual trust mechanism and realize access control, a homomorphic encryption method is utilized to realize protection of data security, a homomorphic operation method is utilized to realize'availability and invisibility 'of cross-domain data processing, and a data local cloud computing facility is utilized to solve the problems of homomorphic operation computing power and storage consumption.

Description

Technical Field

[0001] The present invention relates to the field of computing methods, and in particular to a cross-domain data compliance and mutual trust computing method. Background Art

[0002] Global integration is a concept as well as a phenomenon of human social development. Specifically, it refers to the increasing deep integration and interdependence in multiple fields such as politics, economy, culture, and society among countries and regions around the world, forming an organic whole on a global scale.

[0003] With the development of information technology and its widespread application around the world, it has provided a material and technological foundation for global integration. In particular, the development of Internet technology has greatly facilitated cross-domain information communication and operations among countries and regions. However, due to the restrictions on the protection of data information laws between regions, the current cross-domain data exchange calculation method is to use blockchain, trusted computing and other technologies to achieve cross-domain data processing through transmission algorithms without moving data. However, there are still the following problems in cross-domain data exchange:

[0004] 1. Data processing efficiency and cost issues: Although existing technologies can process data without moving it, they often rely on complex algorithm transmission or frequent on-chain interactions, which may lead to slow processing speeds, especially in large data processing scenarios, where efficiency issues are more prominent. At the same time, the high operating costs (such as gas fees) and energy consumption of blockchain technology itself may limit the economic and sustainability of its large-scale application.

[0005] 2. Homomorphic encryption and computing application limitations: Although homomorphic encryption can achieve "available but invisible" data, in actual applications, the computing efficiency of fully homomorphic encryption is low and it cannot reach the practical level for complex operations. Although partial homomorphic encryption improves efficiency, it compromises the comprehensiveness of data protection. The application depth and breadth of this technology in existing technologies may be insufficient, and it has not been fully optimized to meet the needs of efficient and secure data processing.

[0006] 3. Limitations of cross-domain mutual trust mechanisms: Although blockchain technology helps build trust between cross-domain organizations, existing models may focus more on data verification and traceability, and do not adequately consider the adaptability to dynamically changing laws and regulations, the coordination mechanism for cross-domain policy differences, and the interoperability between different blockchain systems, resulting in difficulty in flexibly responding to complex compliance environments in actual applications.

[0007] 4. Data filtering and privacy protection details: Although the research model of Yunnan University of Finance and Economics can filter sensitive data, the details of how to accurately identify sensitive information in a cross-domain environment and balance data utilization and privacy protection may not be clear enough, and lack detailed adaptation to the specific requirements of laws and regulations in different regions.

[0008] 5. Data processing is limited by user authorization. In the era of big data, it is difficult to adapt to small organizations in wider regions to achieve convenient cross-regional cross-domain data computing. Summary of the invention

[0009] In order to solve the above technical problems, the present invention, under the premise of the protection requirements of the laws and regulations of the two places for relevant data, uses the alliance blockchain to build a cross-domain organizational mutual trust mechanism and implement access control, uses homomorphic encryption methods to achieve data security protection, uses homomorphic computing methods to achieve "available but invisible" cross-domain data processing, uses data local cloud computing facilities to solve the problems of homomorphic computing power and storage consumption, and constructs a cross-domain data compliance mutual trust computing method to realize cross-regional data processing.

[0010] The technical solution adopted by the present invention is: a cross-domain data compliance mutual trust calculation method, comprising the following steps:

[0011] S1: Cross-domain data access control based on blockchain to achieve consensus mechanism establishment and authority management among cross-domain organizations;

[0012] S2: Cross-domain organization key chaining, chaining the cross-domain organization's file encryption public key, homomorphic encryption public key, and digital signature public key to the blockchain alliance chain to ensure the credibility and security of the public key;

[0013] S3: Differentiate cross-domain data compliance, using machine learning, expert review, and deep learning to classify cross-domain data into private data and public data.

[0014] S4: Build a cross-domain data exchange model to ensure the security, certainty, integrity and compliance of data exchange;

[0015] S5: Use blockchain to upload cross-domain data to the chain, encrypt the data through blockchain smart contracts and store it in IPFS, and upload the IPFS address hash value to the chain;

[0016] S6: Perform homomorphic operations on cross-domain data, perform homomorphic operations on confidential privacy data on cloud computing servers, and upload the operation results to IPFS;

[0017] S7: Put the homomorphic operation result on the chain, sign and encrypt the operation result through the blockchain node signature private key, and then put the hash value of the result file and the IPFS address hash value on the chain;

[0018] S8: Obtain the homomorphic operation result, obtain the result address from the blockchain, download the result file from IPFS, decrypt and verify it for business update.

[0019] As a further technical solution of the present invention: the cross-domain organization key is chained. In this stage, the file encryption public key, homomorphic encryption public key and digital signature public key of the cross-domain organization are chained on the alliance chain of the blockchain. Since the alliance chain has established a consensus mechanism and the blockchain has the non-repudiation and non-tamperability, after the three public keys are chained, the credibility of the public key issued across domains and the security of the keys can be ensured.

[0020] As a further technical solution of the present invention: the cross-domain data compliance distinction, this stage distinguishes between private data and public data during the cross-domain data transmission process. According to cross-domain laws and regulations, cross-domain data is classified to distinguish between private data and public data. This part consists of three parts. One part is human machine learning, which automatically classifies cross-domain data. The second part is the expert mode, and experts review and approve the results of machine learning distinction. In the third part, deep learning re-trains the expert mode approval results to improve the accuracy of cross-domain data grading and classification next time. This stage mainly solves the adaptability of dynamically changing laws and regulations during cross-domain data transmission, and the coordination mechanism of cross-domain policy differences, which makes it difficult to flexibly respond to complex compliance environments in practical applications.

[0021] As a further technical solution of the present invention: the construction of the cross-domain data exchange model, this stage is to ensure the security, certainty, integrity and compliance of cross-domain data exchange. The work to be completed includes the following parts: first, obtaining the other party's file encryption public key on the blockchain to ensure file security; second, using its own homomorphic encryption public key to encrypt private data; third, the formation of cross-border data exchange XML. Merge the private data and public data in the secret state into an XML; fourth, file signing: use its own digital signature private key to sign the XML file; fifth, file encryption: obtain the other party's file encryption public key on the blockchain to encrypt the XML file. Finally, a cross-border data exchange model is formed.

[0022] As a further technical solution of the present invention: the cross-domain data is uploaded to the chain by using blockchain. This stage is conducive to blockchain smart contracts. The cross-border data XML is transmitted to IPFS (IPFS is a file storage system, also known as the interstellar file storage system. It is a distributed file transfer protocol based on file content to find the file address), and the IPFS address hash value data is uploaded to the chain at the same time. The steps include: first, data integrity assurance, obtaining the hash value of the file; second, the cross-border data exchange file is transmitted to the IPFS of the cross-border organization, and the hash value of the IPFS address of the cross-border data exchange file is formed; third, the hash value of the file and the hash value data of the file address are uploaded to the chain by using blockchain smart contracts. Only the hash address of the file is saved on the blockchain, and using IPFS to store public data is conducive to compressing the size of the blockchain public account book.

[0023] As a further technical solution of the present invention: the cross-domain data is homomorphically operated. At this stage, the cross-domain data receiver takes the cross-border privacy data from IPFS, uploads it to the cloud computing server of the cross-domain organization and performs homomorphic operation. Finally, the blockchain consensus mechanism is used to upload the homomorphic operation result to IPFS, and the homomorphic operation result is uploaded to the chain. The steps of the cross-domain data receiver are as follows: First, obtain the file address. Obtain the IPFS address of the file and the hash value of the file integrity from the blockchain; second, file integrity verification. Obtain the XML file from IPFS according to the address, and compare the file hash with the hash value on the chain to verify the integrity of the file; third, file decryption. The cross-domain organization file receiver uses the private key of its own file to decrypt the file; fourth, file determinism verification. Obtain the file signature public key of each sender from the chain, decrypt the file using the public key, and determine that the file is the file transmitted by the cross-border organization. Fifth, the confidential data is uploaded to the cloud, and the privacy data after homomorphic encryption is obtained from the cross-border data exchange file and uploaded to the cloud computing server of the cross-border organization; sixth, the homomorphic operation method is used to perform homomorphic operation on the privacy data of each party in a confidential state. The introduction of cloud computing servers solved the problem of computing power consumption caused by homomorphic encryption operations.

[0024] As a further technical solution of the present invention: the homomorphic operation result is put on the chain, and in this stage, the homomorphic operation result is uploaded to IPFS, and the IPFS address of the operation result file is put on the chain. The steps include: first, the certainty of the homomorphic operation result is guaranteed. The blockchain node signature private key is used to sign the homomorphic operation result XML file to ensure the certainty of the file; second, the security of the homomorphic operation result file is guaranteed, and the homomorphic operation result file is encrypted using the file public key of the cross-border organization; third, the integrity of the homomorphic operation result file is guaranteed. The homomorphic operation result file is hashed to form a file integrity hash value, and the file is uploaded to IPFS to obtain the hash value of the file address; fourth, the homomorphic operation result data is put on the chain. The file hash value and the file IPFS address hash value data are put on the chain.

[0025] As a further technical solution of the present invention: the homomorphic operation result is obtained. In this stage, the homomorphic operation result address is obtained from the blockchain, the homomorphic operation result file is obtained according to the address, and the operation result is decrypted using the homomorphic operation private key and the localized business process is updated. It mainly includes the following aspects: First, the homomorphic operation result file is obtained, the file integrity hash value and the IPFS address hash value are obtained from the chain, and the homomorphic operation result file is obtained from the IPFS. Second, the integrity check of the homomorphic operation result file. The hash of the homomorphic operation result file obtained from the IPFS is compared with the file integrity hash value on the chain to ensure the integrity of the file. Third, the decryption of the homomorphic operation file result. The homomorphic operation result file is decrypted using its own file private key; fourth, the deterministic check of the homomorphic operation result file. The signature of the file is verified using the sender's file signature public key to ensure the certainty of the file; fifth, the decryption of the homomorphic operation result. The homomorphic operation result is obtained from the homomorphic operation file result, and the result is decrypted using its own homomorphic operation private key. In the next step, the business system is updated according to the decryption result according to the business process.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] 1. Use alliance chains and smart contracts to achieve cross-domain consensus and mutual trust in data access control. On the one hand, the alliance blockchain is only open to cross-domain organizations that have joined the alliance chain, ensuring that cross-domain data processing is limited to alliance cross-domain organizations and establishing a mutual trust relationship between cross-domain organizations; on the other hand, in view of the fact that the data within the cross-domain organization is open to different data requesters to different degrees, smart contracts are used to achieve access control, and access rights are put on the chain at the same time, ensuring that data access rights are traceable, tamper-proof, and decentralized.

[0028] 2. The Interstellar File Interaction System IPFS has built a cross-domain data processing and storage system. The cross-domain data files are stored in the IPFS system, and only the data fingerprint is stored in the blockchain account book. The cross-domain data requesting party with authority accesses the data through the address, which reduces the amount of data in the blockchain consensus account book and ensures the efficiency of blockchain transactions.

[0029] 3. When processing cross-domain data, ensure the security of cross-domain data processing. First, use the digital signature private key on the chain to ensure the issuer of the cross-border data file; second, the data processor uses the public key on the chain to ensure that only the recipient can decrypt the data file; third, cross-border organizations use the same homomorphic encryption public key and use homomorphic operations to process private data.

[0030] 4. In the present invention, only the cross-domain data requester has the homomorphic computing private key. On the one hand, when the cross-domain data is transmitted out of the country, the confidential data operator cannot crack it; on the other hand, the cross-domain data requester only obtains the homomorphic computing result, which does not involve private data, ensuring that private data is protected by law and realizing cross-domain data compliance and mutual trust computing. At the same time, since homomorphic computing requires high computing power, local cloud computing services can alleviate the computing power problem of homomorphic computing. The use of blockchain to chain the computing results ensures that the computing results can be traced and cannot be tampered with. Homomorphic computing realizes the "available but invisible" of cross-domain data.

[0031] 5. In view of the diversity of laws and regulations and data classification, the present invention adapts the method of distinguishing private data from public data according to the changes in laws and regulations to ensure that cross-domain data exchange does not violate the laws and regulations between regions. At the same time, the cross-domain data transmission model can be adjusted to ensure the stability of the core data model.

[0032] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0034] Figure 1 It is a cross-domain data compliance calculation flow chart of the present invention.

[0035] Figure 2 This is the cross-domain data exchange access control diagram of the blockchain of the present invention.

[0036] Figure 3 It is the design diagram of smart contract data access control of the present invention.

[0037] Figure 4 It is the digital signature encryption flow chart of the present invention.

[0038] Figure 5 It is a flow chart of digital signature verification in the present invention.

[0039] Figure 6 This is the CBO file security design diagram based on blockchain in the present invention.

[0040] Figure 7 This is the multi-CBO file security design diagram based on blockchain in the present invention.

[0041] Figure 8 This is a diagram of the cross-domain data differentiation architecture in the present invention.

[0042] Fig. 9 It is the homomorphic operation result acquisition and decryption diagram in the present invention.

[0043] Fig.10 It is the optimization design diagram of homomorphic operation in the present invention. DETAILED DESCRIPTION

[0044] The following is a clear and complete description of the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. For detailed descriptions of the symbols shown in the following embodiments, please see the table below:

[0045] Symbol Description Table

[0046]

[0047]

[0048]

[0049] The technical solution of the present invention is: a cross-domain data compliance mutual trust calculation method, such as Figure 1 As shown, it includes the following steps:

[0050] S1: Cross-domain data access control based on blockchain. In the process of cross-domain data exchange, access control between cross-domain organization nodes is established according to the business, and a set of permission management system is provided to achieve the establishment of a consensus mechanism between cross-domain organizations. At the same time, it can manage the read and write control of the business and data level between cross-domain organizations to ensure permission control in the process of data filtering and privacy protection details.

[0051] S2: Cross-domain organization key chaining. The cross-domain organization's file encryption public key, homomorphic encryption public key, and digital signature public key are chained on the blockchain alliance chain. Since the alliance chain has established a consensus mechanism and the blockchain is non-repudiable and tamper-proof, after the three public keys are chained, the credibility of cross-domain public key issuance and the security of the key can be ensured.

[0052] S3: Compliance differentiation of cross-domain data. According to cross-domain laws and regulations, cross-domain data is classified to distinguish between private data and public data. This part consists of three parts. One part is human machine learning, which automatically classifies cross-domain data. The second part is the expert mode, in which experts review and approve the results of machine learning. In the third part, deep learning retrains the results of expert mode approval to improve the accuracy of cross-domain data classification next time. This stage mainly solves the problem of adaptability to dynamically changing laws and regulations during cross-domain data transmission and the coordination mechanism of cross-domain policy differences, which makes it difficult to flexibly respond to complex compliance environments in practical applications.

[0053] S4: Build a cross-domain data exchange model. To ensure the security, certainty, integrity and compliance of cross-domain data exchange, the following work needs to be completed: First, obtain the other party's file encryption public key on the blockchain to ensure file security; second, use its own homomorphic encryption public key to encrypt private data; third, cross-border data exchange XML is formed. Merge the private data and public data in a secret state into an XML; fourth, file signing: use its own digital signature private key to sign the XML file; fifth, file encryption: obtain the other party's file encryption public key on the blockchain to encrypt the XML file. Finally, a cross-border data exchange model is formed.

[0054] S5: Cross-domain data on-chain. Blockchain is used to put cross-domain data on-chain. This stage is conducive to blockchain smart contracts. The cross-border data XML is transferred to IPFS. The IPFS is a file storage system, also known as the interstellar file storage system. It is a distributed file transfer protocol that finds file addresses based on file content, and at the same time, the IPFS address hash value data is put on-chain. The steps include: first, data integrity assurance, obtaining the hash value of the file; second, the cross-border data exchange file is transferred to the IPFS of the cross-border organization, and the hash value of the IPFS address of the cross-border data exchange file is formed; third, the hash value of the file and the hash value data of the file address are put on-chain using blockchain smart contracts. Only the hash address of the file is saved on the blockchain. Using IPFS to store public data is conducive to compressing the size of the blockchain public ledger.

[0055] S6: Perform homomorphic operations on cross-domain data. In this stage, the cross-domain data receiver takes the cross-border private data from IPFS, uploads it to the cloud computing server of the cross-domain organization and performs homomorphic operations. Finally, the blockchain consensus mechanism is used to upload the homomorphic operation results to IPFS, and the homomorphic operation results are uploaded to the chain. The steps for the cross-domain data receiver are as follows: First, obtain the file address. Obtain the IPFS address of the file and the hash value of the file integrity from the blockchain; second, file integrity verification. Obtain the XML file from IPFS according to the address, and compare the file hash with the hash value on the chain to verify the integrity of the file; third, file decryption. The cross-domain organization file receiver uses the private key of its own file to decrypt the file; fourth, file determinism verification. Obtain the file signature public key of each sender from the chain, decrypt the file using the public key, and determine that the file is the file transmitted by the cross-border organization. Fifth, upload the confidential data to the cloud, obtain the homomorphically encrypted private data from the cross-border data exchange file and upload it to the cloud computing server of the cross-border organization; sixth, use the homomorphic operation method to perform homomorphic operations on the private data of each party in a confidential state. The introduction of cloud computing servers solved the problem of computing power consumption caused by homomorphic encryption operations.

[0056] S7: Upload the homomorphic operation results to the chain. In this stage, the homomorphic operation results are uploaded to IPFS, and the IPFS address of the operation result file is uploaded to the chain. The steps include: First, the determinism of the homomorphic operation results is guaranteed. The blockchain node signature private key is used to sign the homomorphic operation result XML file to ensure the certainty of the file; second, the security of the homomorphic operation result file is guaranteed, and the homomorphic operation result file is encrypted using the file public key of the cross-border organization; third, the integrity of the homomorphic operation result file is guaranteed. The homomorphic operation result file is hashed to form a file integrity hash value, and the file is uploaded to IPFS to obtain the hash value of the file address; fourth, the homomorphic operation result data is uploaded to the chain. The file hash value and the file IPFS address hash value data are uploaded to the chain.

[0057] S8: Get homomorphic operation results. In this stage, get the homomorphic operation result address from the blockchain, get the homomorphic operation result file according to the address, use the homomorphic operation private key to decrypt the operation result and update the localized business process. It mainly includes the following aspects: First, get the homomorphic operation result file, get the file integrity hash value and IPFS address hash value from the chain, and get the homomorphic operation result file from IPFS. Second, the integrity check of the homomorphic operation result file. Compare the hash of the homomorphic operation result file obtained from IPFS with the file integrity hash value on the chain to ensure the integrity of the file. Third, decrypt the homomorphic operation file result. Decrypt the homomorphic operation result file using its own file private key; Fourth, the deterministic check of the homomorphic operation result file. Use the sender's file signature public key to verify the signature of the file to ensure the determinism of the file; Fifth, decrypt the homomorphic operation result. Get the homomorphic operation result from the homomorphic operation file result, use its own homomorphic operation private key to decrypt the result, and then update the business system according to the decryption result according to the business process.

[0058] The following is a detailed description of the cross-domain data access control process based on blockchain. First, data is stored using IPFS, and data calculations are completed using off-chain calculations. The blockchain plays the role of access control. After the cross-border data passes the access control of the blockchain, it is stored off-chain. Specifically, when cross-border data needs to be processed, the cross-border organization must first access the blockchain, and the blockchain performs access control to determine whether there is mutual trust between cross-border organizations, whether there is data reading permission, and calculation permission, and then process the data. Figure 2As shown, the cross-domain data compliance computing alliance involves multiple cross-domain organizations. The data access control principle of the present invention is "the data generator provides authorized data access rights", so the data access control design includes two parts. One is the allocation of data access control rights, that is, when generating data, it is necessary to define which party the data can be provided to for access; the second is data access control, that is, only the data demander with data access rights can obtain data according to the rights. There are several problems in data access control. First, in terms of business, data access allocation changes frequently, such as department changes, policy changes, business changes, system changes, etc., which will affect data access rights; second, at the data level, the data generator requires "one number and one source", that is, data generation can only be given to multiple data demanders through access control at the same time after the alliance is generated, rather than generating different data for different data demanders; third, at the technical level, there are multiple server entities in the cross-domain organization, and the IP address and domain name address of the server before have the possibility of frequent changes. The above three problems in data access control are analyzed to show that the data generator is fixed and the data demander has the possibility of frequent changes. Therefore, combining the consensus ledger and smart contract features of blockchain, the present invention stores the data permission generator and its allocation rules in the consensus ledger of blockchain, stores the data access rules in the smart contract, and installs them in each blockchain node at the same time. The immutability of blockchain is used to ensure that each cross-domain data access complies with the access rules.

[0059] Further Figure 3 As shown in the figure, the blockchain consensus ledger is a block hash address, a business hash address, and a server key form. The block hash address is generated by the blockchain, the business hash address is generated by the data generator according to the cross-domain data exchange business, and the server key form stores the server key value related to this cross-domain data exchange business in the blockchain channel. The consensus ledger of the blockchain only saves the cross-domain data exchange business, which servers can provide external data access. The blockchain smart contract establishes a link relationship with the consensus ledger through the business hash address. At the same time, the smart contract defines the real address of the server, as well as the data type read and write permissions that the corresponding address can access to the server.

[0060] Furthermore, the present invention uses digital signature technology to protect the integrity and certainty of data units between cross-domain organizations during cross-border data file transmission. Specifically, the file recipient can use the digital signature to authenticate the cross-border data transmission identity and verify the data source; the file recipient can use the data signature decryption result to verify the integrity of the cross-border data transmission unit; only the data sender can sign the data unit. Furthermore, the digital signature process is as follows: Figure 4As shown, first, the hash value of the cross-border data is obtained by using a hash function; second, the hash value is encrypted using the private key of the information sender of the cross-domain data transmission organization, and the encryption result is used as the cross-border data summary; third, the cross-border data and the cross-border data summary are merged into new cross-border transmission data. The digital signature verification process is as follows Figure 5 The diagram includes three steps: first, obtaining the cross-border data summary, decrypting it using the public key of the data sender, and obtaining the decrypted hash value; second, obtaining the cross-border data, and obtaining the comparison hash value using the hash function; third, comparing the decrypted hash value and the comparison hash value to see if they are equal. If they are equal, it means that the file is complete and it is confirmed that the file was sent by the sender.

[0061] Furthermore, the CCAC implements file security assurance such as Figure 6 As shown: Step 1: Public key is uploaded to the blockchain, and each CBO broadcasts P to the blockchain File_EN , through smart contracts to achieve P File_EN On-chain. BC Submit P to the blockchain File_EN On-chain request, other alliance chains Confirm the newly added file encryption public key. When more than 51% of the nodes confirm the block information, the public key block is successfully created. Step 2: Use the public key. When CBO ～ When sending a cross-domain data exchange file to CBO, the blockchain is requested to send CBO’s P File_EN After more than 51% of the nodes confirm the public key usage request, CBO ～ To obtain P File_EN , while the blockchain records CBO ～ Using P File_EN Recording Step 3: File Encryption, CBO ～ Get P File_EN Afterwards, using P File_EN , for XML CBO Encrypt the file and finally form Step 4: File decryption, CBO first obtains it from IPFS Using PK File_EN Decrypt the file and perform cross-domain data exchange calculations.

[0062] Further Figure 7 As shown: When the CCAC needs to form a cross-domain data exchange file for multiple CBOs, it first uses the P File_EN Encrypt the data and transmit it to CBO1, which uses its own PK File_EN After decrypting the data, in XML CBO After adding CBO1 data, request CBO2's P File_EN , using CBO2 PFile_EN Encrypt the data and transmit it to CBO2. After CBO2 obtains the data, it uses its own PK File_EN Decrypting data in XML CBO Add CBO2 data, and repeat this process until the final XML is completed according to the cross-domain data exchange requirements. CBO , transmitted to CBOn, using CBOn's P File_EN form

[0063] The above design applies blockchain to P File_EN The creation and acquisition process of P File_EN All operations will be recorded in the block, ensuring that P File_EN On the other hand, asymmetric encryption technology is used to ensure the traceability and authenticity of PK File_EN Only the data recipient can decrypt the data and obtain the data information.

[0064] Strategy for distinguishing private data from public data. Cross-domain data exchange involves many aspects of data content. According to the laws and regulations of various countries on cross-domain data exchange, data can be divided into two categories, namely public data and private data. It is of great significance to distinguish data. First, at the legal level, the laws of various countries clearly stipulate that private data shall not be exported. Second, at the technical level, homomorphic computing requires large storage resources, strong computing power, and long computing time. It is not suitable to perform homomorphic computing on large amounts of data. Therefore, only performing homomorphic computing on necessary private data can save computing resources.

[0065] The distinction between public data and private data includes two parts: one is the collection of data distinction standards, that is, through cross-border data collection from various departments, the data items of public data are determined; the other is data distinction, that is, according to the standards, public data and private data are distinguished. The data distinction architecture designed by the present invention is as follows Figure 8 Shown: CCAC's S BS Setting up the Data Partition Subsystem DDS BS , S BC Setting up the public data acquisition subsystem DAS BC .DDS BS Deployed on S BS It has the following advantages: First, it ensures the security of privacy data. BS It is a business system server, and the private data in it cannot be exported. BS The business system belongs to the business department, which can redeploy data differentiation strategies according to business rules and local laws and regulations. BC Deployed on S BC It has the following advantages: First, it is convenient to access public data. BCIt is part of the blockchain node, and it is more convenient for alliance nodes to access its data division standards. Second, it is conducive to the update of public data standards. BC As a blockchain node for CBO to realize cross-domain data exchange, XML CBO Need to pass S BC Broadcast to blockchain, parse XML CBO Distinguish between private data and public data, determine one number and one source, and update DAS BC , which can ensure the accuracy of public data division.

[0066] Furthermore, the cross-domain data exchange includes public data and privacy data Swap the two parts. Strictly protected by laws and regulations of various countries, Without the consent of the data subject, data shall not be transferred abroad. Based on the provisions of the above legal provisions, the present invention introduces a homomorphic computing method to After homomorphic encryption, cross-border Homomorphic operations are performed to achieve the purpose of cross-domain data exchange. It needs to ensure the following three points: First, Transmitted from CBO to CBO ～ After that, CBO~ cannot be obtained through the key The second is CBO ~ to obtain After the data is collected, CBO can ensure that it can be provided according to the cross-domain data exchange requirements. support and Perform homomorphic operations; third, the homomorphic operation results are generated Only cross-domain data exchange demand side Corresponding to the above three points, the present invention combines the characteristics of blockchain that cannot be tampered with and designs the following scenarios: First, the homomorphic encryption public key P FHE On-chain. CBO will FHE To meet the CBO ～ Get P FHE , to one's own Perform homomorphic encryption to achieve and Perform homomorphic operations. Second, homomorphic operations and homomorphic operation results On-chain to meet CBO acquisition Realize cross-domain data exchange. The third is to obtain and decrypt homomorphic operation results.

[0067] Further Fig. 9 As shown: Each CBO uses its own P FHE Encrypted data is sent to CBOn's S C_FHEAt the same time, CBOn uses the P of each CBO according to the needs of each CBO. FHE Encrypt your own data and send it to S C_FHE , S C_FHE After homomorphic operation, the result is returned to each CBO, and the CBO uses its own PK FHE Decrypt the homomorphic operation results to achieve cross-border data exchange. The above method has the following advantages: First, data exchange complies with laws and regulations. On the one hand, each CBO transmits to CBOn’s S C_FHE of The P of each CBO is used. FHE CBOn has no PK FHE The data cannot be decrypted, so the encrypted data does not involve privacy and cannot be cracked except by CBO. C_FHE Within the territory of CBOn, there is no data outflow, and this method does not violate the provisions of laws and regulations that privacy data cannot be out of the country; secondly, cross-border data exchange is achieved. Homomorphic encryption methods support homomorphic operations, and the results of homomorphic operations are Can only use CBO PK FHE Decryption enables cross-border data exchange.

[0068] Further Fig.10 As shown in the figure, homomorphic operations are divided into three parts: homomorphic addition, homomorphic multiplication, and other complex calculations. Homomorphic addition and homomorphic multiplication are completed in CBOn, and other complex calculations are sent back to CBO. After decryption by CBO, the decrypted result is operated on the plaintext, and then the result is homomorphically encrypted and sent back to CBOn for homomorphic operation. The optimization strategy of homomorphic operation is to convert full homomorphic operation into semi-homomorphic operation to improve the instruction cycle. Semi-homomorphic operation has an early origin. In terms of computing resources, it consumes less than full homomorphic operation and has a faster instruction cycle. The second is to hand over complex operations other than addition and multiplication to plaintext operation to improve the instruction cycle. The optimization strategy needs to ensure that the certainty, integrity, and security of homomorphic operation data are guaranteed by the blockchain network.

Claims

1. A cross-domain data compliance mutual trust calculation method, characterized in that , including the following steps: S1: Cross-domain data access control based on blockchain to achieve consensus mechanism establishment and authority management among cross-domain organizations; S2: Cross-domain organization key chaining, chaining the cross-domain organization's file encryption public key, homomorphic encryption public key, and digital signature public key to the blockchain alliance chain to ensure the credibility and security of the public key; S3: Differentiate cross-domain data compliance, using machine learning, expert review, and deep learning to classify cross-domain data into private data and public data. S4: Build a cross-domain data exchange model to ensure the security, certainty, integrity and compliance of data exchange; S5: Use blockchain to upload cross-domain data to the chain, encrypt the data through blockchain smart contracts and store it in IPFS, and upload the IPFS address hash value to the chain; S6: Perform homomorphic operations on cross-domain data, perform homomorphic operations on confidential privacy data on cloud computing servers, and upload the operation results to IPFS; S7: Put the homomorphic operation result on the chain, sign and encrypt the operation result through the blockchain node signature private key, and then put the hash value of the result file and the IPFS address hash value on the chain; S8: Obtain the homomorphic operation result, obtain the result address from the blockchain, download the result file from IPFS, decrypt and verify it for business update.

2. The cross-domain data compliance mutual trust calculation method according to claim 1 is characterized in that: The S1 establishes access control between cross-domain organization nodes based on the business, provides a set of permission management system, realizes the establishment of a consensus mechanism between cross-domain organizations, and can manage the read and write control of the business and data levels between cross-domain organizations to ensure permission control in the process of data filtering and privacy protection details.

3. The cross-domain data compliance mutual trust calculation method according to claim 1 is characterized in that: The S2 cross-domain organization key is chained, and the files of the cross-domain organization are chained on the alliance chain of the blockchain through the file encryption public key, homomorphic encryption public key, and digital signature public key, ensuring the credibility of the public key issued across domains and ensuring the security of the key.

4. The cross-domain data compliance mutual trust calculation method according to claim 1 is characterized in that: The S3 cross-domain data compliance distinction is as follows: S31: Automatically classify cross-domain data through machine learning; S32: Enable the expert mode, and then the expert will review and approve the machine learning differentiation results; S32: Retrain and learn the expert mode approval results to improve the accuracy of cross-domain data grading and classification next time.

5. The cross-domain data compliance mutual trust calculation method according to claim 1 is characterized in that: The specific steps of model construction in S4 are: S41: Obtain the other party’s file encryption public key on the blockchain to ensure file security; S42: Encrypt private data using its own homomorphic encryption public key; S43: Merge the private data and public data in a confidential state into an XML file; S44: Sign the XML document using its own digital signature private key; S45: Obtain the other party’s file encryption public key on the blockchain to encrypt the XML file and form a cross-border data exchange model.

6. The cross-domain data compliance mutual trust calculation method according to claim 1 is characterized in that: The specific steps of S5 using blockchain to upload cross-domain data to the chain are: S51: Obtain the hash value of the file to ensure data integrity; S52: Transmit the cross-border data exchange file to the IPFS of the cross-border organization, and form a hash value of the IPFS address of the cross-border data exchange file; S53: Use blockchain smart contracts to upload the hash value of the file and the hash value data of the file address to the chain.

7. The cross-domain data compliance mutual trust calculation method according to claim 1 is characterized in that: The specific steps of the S6 cross-domain data homomorphic operation are: S61: Obtain the IPFS address of the file and the hash value of the file integrity from the blockchain; S62: Get the XML file from IPFS according to the address, and compare the hash of the file with the hash value on the chain to verify the integrity of the file; S63: The cross-domain organization file recipient decrypts the file using its own file's private key; S64: Obtain the file signature public key of each sender from the chain, decrypt the file using the public key, and confirm that the file is the file transmitted by the cross-border organization; S65: Obtain homomorphically encrypted private data from the cross-border data exchange file and upload it to the cloud computing server of the cross-border organization; S66: Use homomorphic computing methods to perform homomorphic computing on the private data of all parties in a confidential state.

8. The cross-domain data compliance mutual trust calculation method according to claim 1 is characterized in that: The specific steps of uploading the homomorphic operation results to the chain in S7 are: S71: Use the blockchain node signature private key to sign the homomorphic operation result XML file to ensure the certainty of the file; S72: Encrypt the homomorphic operation result file using the file public key of the cross-border organization; S73: Hash the homomorphic operation result file to form a file integrity hash value, and upload the file to IPFS to obtain the hash value of the file address; S74: Upload the file hash value and file IPFS address hash value data to the chain.

9. The cross-domain data compliance mutual trust calculation method according to claim 1 is characterized in that: The specific steps of obtaining the homomorphic operation result in S8 are: S81: Obtain the file integrity hash value and IPFS address hash value from the chain, and obtain the homomorphic operation result file from IPFS; S82: Compare the hash value of the homomorphic operation result file obtained from IPFS with the file integrity hash value on the chain to ensure the integrity of the file; S83: Decrypt the homomorphic operation result file using its own file private key; S84: Verify the signature of the file using the sender's file signature public key to ensure the authenticity of the file; S85: Obtain the homomorphic operation result from the homomorphic operation file result.

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