Cross-domain data trusted circulation method and system based on block chain

Abstract

The invention provides a cross-domain data trusted circulation method and system based on a block chain, relates to the technical field of data security, and solves the technical problems that in the prior art, a data use right and a control right are disjointed, and the credibility and compliance of an under-chain data calculation process cannot be effectively verified. The method comprises the steps of obtaining a data use request and performing content analysis to obtain analyzed data; performing user permission verification based on the analyzed data, and after the permission verification is passed, obtaining a corresponding target data packet and a data use statement; carrying out verifiable calculation on the target data packet through the trusted calculation node to obtain trusted data and verifiable calculation proof; based on the data use declaration, performing compliance verification on the verifiable calculation proof through the smart contract to obtain a verification result; and when the verification result is passed, granting the access right of the trusted data to the user, generating an access audit log and storing the access audit log. The method and the device are used in a cross-domain data circulation process.

Description

Technical Field

[0001] This application relates to the field of data security technology, and in particular to a method and system for trusted cross-domain data circulation based on blockchain. Background Technology

[0002] In the process of data elementization, the core bottleneck facing cross-organizational and cross-regional data circulation lies in the lack of a trust mechanism. Current mainstream solutions have three fundamental flaws: First, their trust foundation relies on centralized platforms or third-party intermediaries, which poses a single point of failure and the risk of power abuse; second, once data is delivered, the provider loses the ability to effectively control and supervise the data usage process, and cannot constrain its purpose and scope of use; finally, existing blockchain technologies are mostly limited to the static storage of data exchange results, and cannot automatically and veribly verify the compliance of complex off-chain data processing behaviors, the authenticity of computational logic, and the confidentiality of original data, leading to a prominent contradiction between "usable but untrustworthy" data and "circulation leading to loss of control." Summary of the Invention

[0003] This application provides a blockchain-based method and system for trusted cross-domain data circulation, which solves the technical problem that existing technologies rely on centralized trust models, leading to a disconnect between data usage rights and control rights, and making it impossible to effectively verify the trustworthiness and compliance of off-chain data computation processes.

[0004] To achieve the above objectives, this application adopts the following technical solution: Firstly, a blockchain-based method for trusted cross-domain data circulation is provided, including: The data is retrieved using a request and its content is parsed to obtain the parsed data; User permission verification is performed based on the parsed data. After the permission verification is successful, the corresponding target data packet and data usage declaration are obtained. By performing verifiable computations on the target data packet through a trusted computing node, trusted data and verifiable computation proofs are obtained. Based on the data usage statement, the verifiable computation proof is verified for compliance through a smart contract, and the verification result is obtained. When the verification result is successful, the user is granted access to trusted data, and an access audit log is generated and stored.

[0005] Based on the above technical solutions, the blockchain-based cross-domain trusted data circulation method provided in this application achieves significant technical effects by constructing a closed-loop mechanism encompassing "request parsing - permission verification - verifiable computation - on-chain compliance verification - authorized auditing." Firstly, it transforms the traditional trust model relying on centralized institutions in data circulation into a technology-driven trust model where blockchain smart contracts automatically verify and trusted computing nodes generate cryptographic proofs, fundamentally eliminating single-point trust risks. Secondly, through the structured expression and end-to-end transmission of data usage declarations, it enables data providers to have precise control over the purpose, computation method, and output scope of data usage, ensuring that data is "controllable in use." Finally, based on on-chain automated compliance verification and tamper-proof audit logs using verifiable computation proofs, it achieves trusted verification and full traceability of complex off-chain computation processes, resolving the core contradiction of "usable but invisible" and "untrustworthy processes" in cross-domain data circulation, and providing a reliable technical infrastructure for the secure and efficient circulation of data elements.

[0006] In conjunction with the first aspect above, in one possible implementation, the data uses a readable structured strategy declared as uploaded by the data provider, including the purpose of the target data packet, the data calculation algorithm, the calculation logical hash, the output format, access constraints, and data freezing rules.

[0007] In conjunction with the first aspect above, in one possible implementation, the user permission verification based on parsed data includes: Extract users' decentralized identifiers, verifiable credentials, and digital signatures from the parsed data; The verifiable credentials are compared with the status of the credentials pre-existing on the blockchain to obtain the comparison result; Based on access constraints, the decentralized identifier and digital signature are verified through a permission verification smart contract to obtain the verification result. When both the comparison result and the verification result meet the preset permission verification conditions, the permission verification is successful.

[0008] In conjunction with the first aspect above, in one possible implementation, the verifiable computation of the target data packet via a trusted computing node includes: Construct a trusted execution environment and load the target data packet and data usage claims into the trusted execution environment; The target data packet is decrypted and calculated based on the data calculation algorithm to obtain reliable data; A verifiable computational proof is generated based on the computation process data; wherein, the computation process data is the data monitored by the trusted execution environment during the decryption and computation of the target data packet, and the verifiable computational proof includes hardware vendor signature, environmental metric value, data computation hash value, and data trustworthiness.

[0009] In conjunction with the first aspect above, in one possible implementation, the compliance verification of the verifiable computational proof via a smart contract includes: Signature verification of hardware manufacturers' signatures is performed through smart contracts; The environmental metrics are matched and verified against pre-registered environmental trust benchmarks in the blockchain; Compare the calculated hash value of the data with the calculated logical hash value; Compare the data credibility with a preset trust threshold; If the signature verification, matching verification, hash comparison and threshold comparison all meet the preset compliance verification conditions, a verification result indicating that the verification has passed will be generated.

[0010] In conjunction with the first aspect above, in one possible implementation, the method for obtaining the environment trust benchmark value includes: performing a security check on the source code of the data calculation algorithm; after the security check passes, compiling the source code in a specified trusted compilation environment to generate an algorithm executable file; and calculating the cryptographic hash value of the algorithm executable file to obtain the environment trust benchmark value.

[0011] In conjunction with the first aspect above, in one possible implementation, the data freezing rule is triggered by periodically monitoring the trusted computing node; when a hardware vulnerability or data leakage risk is detected in the trusted computing node, the node management smart contract updates the state of the trusted computing node to unavailable and freezes the target data packet.

[0012] In conjunction with the first aspect above, in one possible implementation, the trusted computing node status is updated as follows: hardware vulnerabilities or data leakage risks are compiled into frozen evidence; the frozen evidence is adjudicated according to preset adjudication rules; if the adjudication is successful, the trusted computing node status is set to unavailable; if the adjudication fails, an abnormal signal is generated and the frozen evidence is sent to the node operation and management personnel.

[0013] In conjunction with the first aspect above, in one possible implementation, generating and storing access audit logs includes: when a user accesses trusted data, generating a corresponding access audit log and aggregating it using a Merkle tree; uploading the hash value of the access audit log to the blockchain for storage; wherein the access audit log includes a unique identifier for this data circulation, a decentralized identifier, a hash value of the data usage declaration, a hash value of the verifiable computational proof, a timestamp of the verification result, and the resource consumption of this access.

[0014] Secondly, a blockchain-based cross-domain trusted data circulation system is provided, including a user request processing module, a permission and policy management module, a trusted computing processing module, a blockchain verification module, and an access control and auditing module. The user request processing module is used to obtain data usage requests and parse the content to obtain parsed data; The permission and policy management module is used to verify user permissions based on parsed data, and extract the corresponding target data packet and data usage declaration after the verification is successful. The trusted computing processing module is used to perform verifiable computations on the target data packet through a trusted computing node to obtain trusted data and verifiable computation proofs. The blockchain verification module is used to perform compliance verification on verifiable computational proofs based on data usage statements through smart contracts, and obtain verification results. The access control and auditing module is used to grant users access to trusted data when the verification result is passed, generate access audit logs, and store them.

[0015] This application provides a blockchain-based method and system for trusted cross-domain data circulation. By constructing a collaborative technology system of "structured declaration-driven, trusted execution environment, and automatic verification by blockchain smart contracts," it achieves the following significant results: First, it innovatively transforms data usage strategies into structured declarations that can be parsed and executed across the entire chain, realizing the precise expression and transmission of data usage intentions. Second, by introducing a verifiable computation and proof generation mechanism based on trusted hardware, it provides a publicly verifiable technical foundation for off-chain computation processes while ensuring that the original data is not leaked. Finally, it uses blockchain smart contracts to automatically verify computational proofs in compliance with regulations and establishes a complete audit trail chain, achieving a leap from "result storage" to "trustworthy process verification." Ultimately, it constructs a trust infrastructure in a decentralized environment that spans the entire lifecycle of data circulation, with clear responsibilities and controllable auditability.

[0016] It should be understood that the descriptions of technical features, technical solutions, beneficial effects, or similar language in this application do not imply that all features and advantages can be achieved in any single embodiment. Rather, it is understood that the description of a feature or beneficial effect means that a specific technical feature, technical solution, or beneficial effect is included in at least one embodiment. Therefore, the descriptions of technical features, technical solutions, or beneficial effects in this specification do not necessarily refer to the same embodiment. Furthermore, the technical features, technical solutions, and beneficial effects described in this embodiment can be combined in any suitable manner. Those skilled in the art will understand that embodiments can be implemented without one or more specific technical features, technical solutions, or beneficial effects of a particular embodiment. In other embodiments, additional technical features and beneficial effects may be identified in specific embodiments that do not embody all embodiments. Attached Figure Description

[0017] Figure 1 A system architecture diagram of a blockchain-based cross-domain trusted data circulation system provided for embodiments of this application; Figure 2 A flowchart illustrating a blockchain-based method for trusted cross-domain data circulation is provided in this embodiment of the application. Figure 3 This is a flowchart illustrating another blockchain-based method for trusted cross-domain data circulation, provided as an embodiment of this application. Detailed Implementation

[0018] In the description of this application, unless otherwise stated, " / " means "or," for example, A / B can mean A or B. The "and / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone. Furthermore, "at least one" means one or more, and "multiple" means two or more. The terms "first," "second," etc., do not limit the quantity or order of execution, and "first," "second," etc., do not necessarily imply differences.

[0019] It should be noted that, in this application, the terms "exemplary" or "for example" are used to indicate that something is being described as an example, illustration, or illustration. Any embodiment or design described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design solutions. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0020] The blockchain-based cross-domain trusted data circulation method provided in this application can be applied to, for example... Figure 1 In the blockchain-based cross-domain trusted data circulation system 100 shown, such as Figure 1 As shown, the communication system includes: a user request processing module 10, a permission and policy management module 20, a trusted computing processing module 30, a blockchain verification module 40, and an access control and auditing module 50.

[0021] Among them, the user request processing module 10 is used to obtain data usage requests and perform content parsing to obtain parsed data; The permissions and policy management module 20 is used to verify user permissions based on parsed data, and extract the corresponding target data packet and data usage declaration after the verification is successful. The trusted computing processing module 30 is used to perform verifiable computations on the target data packet through a trusted computing node to obtain trusted data and verifiable computation proofs. The blockchain verification module 40 is used to verify the compliance of verifiable computational proofs based on data usage statements through smart contracts, and obtain the verification results. The access control and auditing module 50 is used to grant users access to trusted data when the verification result is passed, generate access audit logs, and store them.

[0022] To address the technical problems arising from existing technologies' reliance on centralized trust models, which leads to a disconnect between data usage rights and control, and the inability to effectively verify the trustworthiness and compliance of off-chain data computation processes, this application provides a blockchain-based method for trusted cross-domain data circulation. This method includes: The data is retrieved using a request and its content is parsed to obtain the parsed data; User permission verification is performed based on the parsed data. After the permission verification is successful, the corresponding target data packet and data usage declaration are obtained. By performing verifiable computations on the target data packet through a trusted computing node, trusted data and verifiable computation proofs are obtained. Based on the data usage statement, the verifiable computation proof is verified for compliance through a smart contract, and the verification result is obtained. When the verification result is successful, the user is granted access to trusted data, and an access audit log is generated and stored.

[0023] Based on this, the technical problem of existing technologies relying on centralized trust models, which leads to a disconnect between data usage rights and control rights, and makes it impossible to effectively verify the credibility and compliance of off-chain data computation processes, is solved.

[0024] like Figure 2 As shown in the embodiments of this application, the method for trusted cross-domain data circulation based on blockchain includes: S201. Obtain data using the request and parse the content to obtain parsed data.

[0025] For example, data usage requests are received by the system in the form of structured API calls (such as HTTP POST requests). The request body is encapsulated in JSON format and includes the requester's DID (Decentralized Identifier), the unique identifier of the target data resource, the request operation type (such as "statistical analysis" or "model training"), and an accompanying OAuth 2.0 access token or verifiable credential. The content parsing module first verifies the validity of the request format and digital signature, then extracts key fields through the parser and maps them to internal standard data structures (such as mapping the operation type to a predefined algorithm identifier), while verifying the validity of the token and the scope of permissions. Finally, it outputs a parsed data object containing standardized fields for use by the subsequent permission verification module.

[0026] S202. Perform user permission verification based on the parsed data. After the permission verification is successful, obtain the corresponding target data packet and data usage declaration.

[0027] In some implementations, the data uses a readable structured strategy declared as uploaded by the data provider, including the purpose of the target data packet, the data calculation algorithm, the calculation of logical hash, the output format, access constraints, and data freezing rules.

[0028] It should be noted that by transforming legal and commercial terms of use into standardized, programmable machine instructions, a precise and irrefutable "digital contract" basis is provided for subsequent fully automated authorization verification, trusted computing, and compliance verification, thereby technically ensuring the certainty and controllability of the data flow process.

[0029] For example, the data provider creates a machine-readable data use claim in JSON-LD or YAML format via a management console or API. This claim file strictly includes key structured fields corresponding to the claims: purpose of use (explicitly enumerating values, such as "academic research"), data computation algorithm (specifying the specific algorithm name or identifier), computational logical hash (the exact SHA-256 digest value obtained after the algorithm is trustedly compiled), output format (explicitly specifying the data structure or type of the result), access constraints (fine-grained rules defined in a policy language, such as concurrency levels and time windows), and data freeze rules (defining the specific conditions that trigger automatic termination of data access). The complete content of this claim generates a unique hash value and is registered to the blockchain, forming an immutable binding with the target data packet.

[0030] In some implementations, user permission verification is based on parsed data, such as... Figure 3 As shown, it includes: S31. Extract the user's decentralized identifier, verifiable credentials, and digital signature from the parsed data; S32. Compare the verifiable credentials with the status of credentials pre-existing on the blockchain to obtain the comparison result; S33. Based on access constraints, the decentralized identifier and digital signature are verified through the permission verification smart contract to obtain the verification result; S34. When both the comparison result and the verification result meet the preset permission verification conditions, the permission verification is successful.

[0031] It should be noted that the factuality and timeliness of user qualifications are ensured by comparing the chain state of verifiable credentials, and the authenticity and non-repudiation of the operation intent are ensured by verifying the digital signature and DID through smart contracts. The combination of the two completely eliminates the dependence on centralized authentication servers, and builds a trust infrastructure in cross-domain scenarios that respects user sovereignty and meets the data party's need for fine-grained control, realizing a truly decentralized, cryptographic primitive-based dual verification mechanism.

[0032] For example, three key elements are first extracted from the standardized parsed data object: a user-generated DID (e.g., did:ethr:0xabcd...), a verifiable credential issued by an authoritative institution (using the W3C VC-DATA-MODEL standard JWT format), and an ECDSA signature generated using the user's private key for the request parameters. Subsequently, the system queries the credential registration smart contract through blockchain nodes to verify that the credential's hash value exists in the list of valid credentials and that its status has not been revoked, completing the on-chain status comparison. Simultaneously, the permission verification smart contract is triggered. This contract has a built-in access control list and policy engine, and its verification logic includes: verifying whether the DID in the request is within the authorized whitelist of the target data, and verifying through the ecrecover function whether the digital signature was indeed generated by the Ethereum address private key corresponding to the DID. Only when the on-chain credential status shows "valid" and the smart contract returns a result indicating that the signature verification has passed and matches the permissions is the entire permission verification process marked as successful.

[0033] In some implementations, the data freezing rule is triggered by periodically monitoring trusted computing nodes; when a hardware vulnerability or data leakage risk is detected in a trusted computing node, the node management smart contract updates the state of the trusted computing node to unavailable and freezes the target data packet.

[0034] It should be noted that by establishing a dynamic risk response mechanism based on objective evidence and automated execution, and combining external security intelligence with on-chain contract adjudication, continuous measurement of the reliability of trusted computing infrastructure and real-time protection of data assets have been achieved. This greatly reduces the potential risk of large-scale leakage of sensitive data due to underlying hardware vulnerabilities or node breaches, and enhances the resilience and proactive security defense capabilities of the entire circulation system.

[0035] For example, a proactive monitoring service is deployed that periodically (e.g., every 24 hours) requests each registered trusted computing node to submit an updated health certificate report generated by its TEE hardware. This report includes the current firmware's security patch version number and memory integrity metric. The monitoring service verifies two pieces of information using a pre-configured security vulnerability intelligence subscription list (such as a synchronized MITRE CVE database) and an off-chain trusted oracle: first, it checks if the hardware model and version in the report are on the known high-risk vulnerability list; second, it verifies whether the node's current operating environment can still produce valid proofs by repeating the remote authentication process. When either verification fails, the monitoring service sends a signed "risk warning" transaction to the node management smart contract on the blockchain. The contract's built-in adjudication logic, after confirming the signature's validity, automatically executes two atomic operations: first, it updates the target node's status field in the node registry to "unavailable"; then, based on the data packet records processed by the node, it triggers the associated data declaration management contract to change the access status of the relevant data packets to "frozen," thereby immediately preventing all subsequent computation requests based on these data packets.

[0036] In some implementations, the trusted computing node status is updated as follows: hardware vulnerabilities or data leakage risks are compiled into frozen evidence; the frozen evidence is adjudicated according to preset adjudication rules; if the adjudication is successful, the trusted computing node status is set to unavailable; if the adjudication is unsuccessful, an abnormal signal is generated and the frozen evidence is sent to the node operation and management personnel.

[0037] It should be noted that by combining the standardization of risk evidence with an on-chain programmable adjudication process, a transparent, efficient, and collusion-resistant node state governance mechanism has been established. On the one hand, automated adjudication enables rapid response and handling based on solid evidence, greatly shortening the cycle from risk discovery to security isolation. On the other hand, by introducing decentralized human arbitration and anomaly reporting, necessary human review and final decision-making entry points are provided for complex or questionable risk scenarios. This ensures the efficiency of the system's automated operation while avoiding the risk of misjudgment that may result from full automation, thus enhancing the robustness and fairness of the overall management mechanism.

[0038] For example, frozen evidence is structured into a standardized JSON report containing security audit logs of trusted computing nodes obtained through a secure channel (such as scan results recording specific CVE vulnerability numbers) and abnormal behavior monitoring logs (such as verifiable records of unauthorized memory access patterns). The system submits this evidence to a decentralized adjudication smart contract deployed on the blockchain, which pre-defines programmable adjudication rules (e.g., specifying that "if the evidence contains both a confirmed high-risk CVE number and a related abnormal access log, the adjudication is automatically approved"). Upon receiving the evidence, the adjudication contract invokes a multi-signature verification logic managed by multiple pre-selected arbitrators (whose public keys are registered on-chain). If, within a set time, more than a preset threshold (e.g., 3 out of 5 arbitrators) confirm the validity of the evidence with on-chain signatures, the adjudication is automatically approved, and the contract then calls the `setNodeStatus` function of the node management contract to update the target node's status field to "unavailable." If a consensus cannot be reached within the validity period or the evidence is rejected by a majority of arbitrators, the arbitration contract will generate an exception event containing details of the evidence and send the event along with the complete evidence package to the pending work order system of the node operation and management personnel through an integrated messaging service (such as calling the Webhook API of the management platform).

[0039] S203. Verifiable computation is performed on the target data packet through a trusted computing node to obtain trusted data and verifiable computation proof.

[0040] In some implementations, the verifiable computation of the target data packet via a trusted computing node includes: Construct a trusted execution environment and load the target data packet and data usage claims into the trusted execution environment; The target data packet is decrypted and calculated based on the data calculation algorithm to obtain reliable data; A verifiable computational proof is generated based on the computation process data; wherein, the computation process data is the data monitored by the trusted execution environment during the decryption and computation of the target data packet, and the verifiable computational proof includes hardware vendor signature, environmental metric value, data computation hash value, and data trustworthiness.

[0041] It should be noted that by encapsulating the complete computation process in a hardware-protected secure environment and generating a cryptographically strong proof, "computation as proof" is achieved. This allows any third party (especially on-chain smart contracts) to verify the proof without needing to access the original data or reproduce the computation process. They can be certain that the computation was performed correctly on the specified data in a specified and tamper-proof environment, according to the declared algorithm. This ensures data confidentiality throughout the process and provides a solid and efficient technical foundation for automated compliance verification on the chain.

[0042] For example, upon receiving a scheduling instruction, the trusted computing node first initiates a trusted execution environment (TEE) based on Intel SGX technology and loads the target data packet (encrypted using the public key of the TEE) and a data usage claim (in JSON format) into the secure enclave. Within the enclave, the data packet is decrypted using the corresponding private key, and the data is computed strictly according to the "Longitudinal Federated Logistic Regression-V2.1" algorithm specified in the claim to generate the computation result (i.e., trusted data). Subsequently, the monitoring module within the enclave collects key computation process data, including but not limited to: the memory metric (MRENCLAVE) of the loaded algorithm code, the SHA-256 hash sequences of the input and output data, and calls SGX hardware instructions to generate a remote proof report (Intel SGX Quote) signed by the Intel root key. This report serves as verifiable computation proof, containing the hardware vendor's (Intel) signature of the platform identity, the current enclave's environmental metric, the hash digests of the input data and computation logic, and a "data trustworthiness" verification code characterizing the integrity of the computation result and the expected compliance of the computation process.

[0043] S204. Based on the data usage statement, the verifiable computation proof is verified for compliance through a smart contract to obtain the verification result.

[0044] In some implementations, the compliance verification of verifiable computational proofs via smart contracts includes: Signature verification of hardware manufacturers' signatures is performed through smart contracts; The environmental metrics are matched and verified against pre-registered environmental trust benchmarks in the blockchain; Compare the calculated hash value of the data with the calculated logical hash value; Compare the data credibility with a preset trust threshold; If the signature verification, matching verification, hash comparison and threshold comparison all meet the preset compliance verification conditions, a verification result indicating that the verification has passed will be generated.

[0045] It should be noted that by transforming complex trusted computing verification into a series of deterministic on-chain cryptographic operations and comparisons, a fully automated, efficient, and tamper-proof judgment on the compliance of off-chain computing processes is achieved. This not only greatly reduces the cost of manual auditing and the possibility of disputes, but also builds a deep defense system through cross-verification of multiple technical dimensions. This ensures that any anomalies in any link (such as environmental tampering, algorithm replacement, or incomplete calculation results) will be keenly identified and blocked. Thus, at the technical level, it achieves refined and automated measurement and protection of the trustworthiness of data circulation.

[0046] For example, when a verifiable computational proof (a remote proof report generated by Intel SGX hardware) is submitted to the blockchain, the on-chain verification smart contract is automatically triggered and executes the following on-chain verification logic: First, the contract calls the pre-set Intel root public key to verify the authenticity of the hardware manufacturer's signature at the end of the report; second, it parses the metric value (MRENCLAVE) representing the current enclave environment from the report body and compares it with the pre-registered environment trust benchmark value corresponding to the task in the "Trusted Application Registry" on the blockchain, requiring complete consistency; next, it extracts the joint hash of the input data and algorithm code recorded in the report as the data hash value and compares it with the computation logic hash in the data usage statement; simultaneously, it verifies the data trustworthiness represented by the result integrity verification code generated internally by the TEE carried in the report, checking whether it is higher than the system's preset trust threshold (for example, this value must indicate "the computation process was not interrupted abnormally and the result is complete"). Only when all four checks pass will the smart contract generate and record the "verification passed" result in the state variable and trigger the subsequent process.

[0047] In some implementations, the method for obtaining the environment trust baseline value includes: performing a security check on the source code of the data calculation algorithm; after the security check passes, compiling the source code in a specified trusted compilation environment to generate an algorithm executable file; and calculating the cryptographic hash value of the algorithm executable file to obtain the environment trust baseline value.

[0048] It should be noted that by combining socialized code auditing with deterministic automated construction, and solidifying the final output hash value on the blockchain as a recognized trust anchor, the authenticity and integrity of the operating environment of any instance claiming to execute the algorithm in the TEE can be unambiguously verified, thus laying a solid foundation for the entire cross-domain data circulation system of "one audit, trust everywhere".

[0049] For example, the acquisition of the environmental trust benchmark follows a standardized trusted software supply chain process: First, the source code of the data computation algorithm "Longitudinal Federated Logistic Regression-V2.1" must be submitted to an audit committee composed of multiple parties (such as data providers, technical experts, and regulatory representatives). This committee conducts a security review using static code analysis tools (such as SonarQube) and formal verification methods to ensure that it contains no malicious code and that the logic is completely consistent with the data usage claims. After the review is passed, the source code is submitted to a predefined and publicly available trusted compilation environment—typically a digitally signed Docker container image that fixes the operating system version, compiler version (such as GCC10.2), and all dependent libraries. Within this container, the source code is compiled to generate a defined algorithm executable file; subsequently, the system uses the SHA-256 algorithm to calculate the hash value "a1b2c3d4e5f67890", which is then recognized as the environmental trust benchmark. This value, along with information such as the audit report summary and compilation environment fingerprint, is permanently registered in a trusted benchmark registry smart contract on the blockchain through a multi-signed transaction and bound to a specific data usage declaration ID.

[0050] S205. When the verification result is passed, grant the user access to trusted data, generate access audit logs, and store them.

[0051] In some implementations, generating and storing access audit logs includes: when a user accesses trusted data, generating a corresponding access audit log and aggregating it using a Merkle tree; uploading the hash value of the access audit log to the blockchain for storage; wherein the access audit log includes a unique identifier for this data circulation, a decentralized identifier, a hash value of the data usage declaration, a hash value of the verifiable computational proof, a timestamp of the verification result, and the resource consumption of this access.

[0052] It should be noted that by using a hybrid architecture of "on-chain evidence hashing and off-chain details storage," the on-chain storage cost is greatly reduced and the overall throughput of the system is improved while ensuring that all audit records are immutable and publicly verifiable. At the same time, the use of Merkle trees for batch aggregation and verification of logs not only improves the efficiency of evidence storage, but also provides a concise cryptographic proof path for efficiently verifying the authenticity and integrity of a specific audit log in the future. This enables traceable, auditable, and economically feasible full lifecycle management of massive data circulation activities.

[0053] For example, when a user successfully obtains and accesses trusted data (such as decrypted computation results) through an authorized interface, the system generates a structured access audit log in real time. This log records the following fields precisely in JSON format: the unique transaction ID of this transaction (e.g., TXID_2024_12345678), the accessing user's DID (did:ethr:0x9a8b...), the hash value of the data used (0x89c2...), the hash value of the verifiable computational proof used in this computation (0xef01...), the timestamp when the blockchain verification smart contract returned the verification result (20XX-05-20T10:30:00Z), and the resource consumption of this access (based on the CU value returned by the trusted computing node, such as 2.5 CU). The system does not immediately upload the complete log to the blockchain. Instead, it adds it to a log buffer pool to be processed. A background service periodically (e.g., hourly) uses all new logs in the pool as leaf nodes to build a Merkle tree. Then, only the root hash of the Merkle tree is submitted in a transaction and permanently stored in the blockchain's audit and evidence storage smart contract. Meanwhile, the complete audit log file itself is stored in a decentralized storage network (such as IPFS) or a high-availability database, and its content index is associated with the Merkle tree path information.

[0054] Based on the above technical solutions, the blockchain-based cross-domain trusted data circulation method provided in this application achieves the following significant effects by constructing a collaborative technical system of "structured declaration-driven, trusted execution environment-supported, and blockchain smart contract automatic verification": First, it innovatively transforms data usage strategies into structured declarations that can be parsed and executed across the entire chain, realizing the accurate expression and transmission of data usage intentions; second, by introducing a verifiable computation and proof generation mechanism based on trusted hardware, it provides a publicly verifiable technical foundation for off-chain computation processes while ensuring that the original data is not leaked; finally, it automatically verifies computation proofs through blockchain smart contracts and establishes a complete audit trail chain, achieving a leap from "result storage" to "process trusted verification," ultimately constructing a trust infrastructure with clear responsibilities and controllability that spans the entire lifecycle of data circulation in a decentralized environment.

[0055] In one possible implementation, this application embodiment also provides a blockchain-based cross-domain trusted data circulation system, including a user request processing module, a permission and policy management module, a trusted computing processing module, a blockchain verification module, and an access control and auditing module; The user request processing module is used to obtain data usage requests and parse the content to obtain parsed data; The permission and policy management module is used to verify user permissions based on parsed data, and extract the corresponding target data packet and data usage declaration after the verification is successful. The trusted computing processing module is used to perform verifiable computations on the target data packet through a trusted computing node to obtain trusted data and verifiable computation proofs. The blockchain verification module is used to perform compliance verification on verifiable computational proofs based on data usage statements through smart contracts, and obtain verification results. The access control and auditing module is used to grant users access to trusted data when the verification result is passed, generate access audit logs, and store them.

[0056] For example, the system is deployed in a cloud-native environment jointly maintained by multiple participants. Its five core modules collaborate in the form of microservices: the user request processing module acts as a gateway, receiving and standardizing HTTP API requests; the permission and policy management module calls the access control contract on the blockchain to verify the user's DID and verifiable credentials, and extracts the corresponding AES-256 encrypted data packets and associated JSON format data usage claims from distributed storage; the trusted computing processing module dispatches tasks to registered Intel SGX nodes through a scheduler, and the nodes complete data decryption and calculation of the specified algorithm within the enclave, generating a remote proof report with an Intel signature; the blockchain verification module then calls the on-chain verification smart contract, which automatically executes logic such as hardware signature verification, enclave metric comparison with on-chain benchmark, and outputs the verification result; finally, the access control and audit module issues a short-term access token to the user based on the on-chain verification result, if it passes, and simultaneously stores the audit log containing the unique circulation identifier, hash values ​​of each stage and timestamps on the chain after Merkle tree aggregation, while the complete log is stored in IPFS.

[0057] Based on the above technical solution, a fully automated pipeline from request access to authorization audit is constructed through the chain collaboration of five modules and the clear division of trust boundaries. It not only realizes fine control and process verification of data usage rights in a decentralized manner, but also ensures the high availability, scalability and resistance to single points of failure through modular design, providing a plug-and-play and compliant technical infrastructure for cross-organizational data collaboration.

[0058] In implementation, each step of the method provided in this embodiment can be completed by integrated logic circuits in the processor or by instructions in software form. The steps of the method disclosed in the embodiments of this application can be directly manifested as being executed by a hardware processor, or being executed by a combination of hardware and software modules in the processor.

[0059] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented using software programs, implementation can be, in whole or in part, in the form of a computer program product. This computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device containing one or more servers, data centers, etc., that can be integrated with the medium. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state disks (SSDs)).

[0060] Although this application has been described herein in conjunction with various embodiments, those skilled in the art, by reviewing the accompanying drawings, disclosure, and appended claims, will understand and implement other variations of the disclosed embodiments in carrying out the claimed application. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude multiple instances. A single processor or other unit can implement several functions listed in the claims. While different dependent claims may recite certain measures, this does not mean that these measures cannot be combined to produce good results.

[0061] Although this application has been described in conjunction with specific features and embodiments, it is obvious that various modifications and combinations can be made thereto without departing from the spirit and scope of this application. Accordingly, this specification and drawings are merely exemplary illustrations of this application as defined by the appended claims, and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from the spirit and scope of this application. Thus, if such modifications and modifications of this application fall within the scope of the claims of this application and their equivalents, this application is also intended to include such modifications and modifications.

Claims

1. A blockchain-based cross-domain data trusted circulation method, characterized in that, include: The data is retrieved using a request and its content is parsed to obtain the parsed data; User permission verification is performed based on the parsed data. After the permission verification is successful, the corresponding target data packet and data usage declaration are obtained. By performing verifiable computations on the target data packet through a trusted computing node, trusted data and verifiable computation proofs are obtained. Based on the data usage statement, the verifiable computation proof is verified for compliance through a smart contract, and the verification result is obtained. When the verification result is successful, the user is granted access to trusted data, and an access audit log is generated and stored. 2.The blockchain-based cross-domain data trusted circulation method according to claim 1, characterized in that, The data uses a readable structured strategy declared as uploaded by the data provider, including the purpose of the target data packet, the data calculation algorithm, the calculation logical hash, the output format, access constraints, and data freezing rules.

3. The blockchain-based cross-domain trusted data circulation method according to claim 2, characterized in that, The user permission verification based on parsed data includes: Extract users' decentralized identifiers, verifiable credentials, and digital signatures from the parsed data; The verifiable credentials are compared with the status of the credentials pre-existing on the blockchain to obtain the comparison result; Based on access constraints, the decentralized identifier and digital signature are verified through a permission verification smart contract to obtain the verification result. When both the comparison result and the verification result meet the preset permission verification conditions, the permission verification is successful. 4.The blockchain-based cross-domain data trusted circulation method according to claim 2, characterized in that, The verifiable computation of the target data packet through a trusted computing node includes: Construct a trusted execution environment and load the target data packet and data usage claims into the trusted execution environment; The target data packet is decrypted and calculated based on the data calculation algorithm to obtain reliable data; A verifiable computational proof is generated based on the computation process data; wherein, the computation process data is the data monitored by the trusted execution environment during the decryption and computation of the target data packet, and the verifiable computational proof includes hardware vendor signature, environmental metric value, data computation hash value, and data trustworthiness. 5.The blockchain-based cross-domain data trusted circulation method according to claim 4, characterized in that, The compliance verification of verifiable computational proofs via smart contracts includes: Signature verification of hardware manufacturers' signatures is performed through smart contracts; The environmental metrics are matched and verified against pre-registered environmental trust benchmarks in the blockchain; Compare the calculated hash value of the data with the calculated logical hash value; Compare the data credibility with a preset trust threshold; If the signature verification, matching verification, hash comparison and threshold comparison all meet the preset compliance verification conditions, a verification result indicating that the verification has passed will be generated. 6.The blockchain-based cross-domain data trusted circulation method according to claim 5, characterized in that, The method for obtaining the environment trust baseline value includes: performing a security check on the source code of the data calculation algorithm; after the security check is passed, compiling the source code in a specified trusted compilation environment to generate an algorithm executable file; calculating the cryptographic hash value of the algorithm executable file to obtain the environment trust baseline value. 7.The blockchain-based cross-domain data trusted circulation method according to claim 2, characterized in that, The data freezing rule is triggered as follows: the trusted computing node is monitored periodically; when a hardware vulnerability or data leakage risk is detected in the trusted computing node, the node management smart contract updates the state of the trusted computing node to unavailable and freezes the target data packet. 8.The blockchain-based cross-domain data trusted circulation method according to claim 7, characterized in that, The trusted computing node status is updated as follows: hardware vulnerabilities or data leakage risks are compiled into frozen evidence; the frozen evidence is adjudicated according to preset adjudication rules; if the adjudication is successful, the trusted computing node status is set to unavailable; if the adjudication fails, an abnormal signal is generated and the frozen evidence is sent to the node operation and management personnel. 9.The blockchain-based cross-domain data trusted circulation method according to claim 1, wherein, The process of generating and storing access audit logs includes: generating corresponding access audit logs when a user accesses trusted data and aggregating them using a Merkle tree; uploading the hash value of the access audit logs to the blockchain for storage; wherein the access audit logs include a unique identifier for this data circulation, a decentralized identifier, a hash value of the data usage declaration, a hash value of the verifiable computational proof, a timestamp of the verification result, and the resource consumption of this access.

10. The blockchain-based cross-domain data trusted circulation system of claim 1, wherein, It includes a user request processing module, a permission and policy management module, a trusted computing processing module, a blockchain verification module, and an access control and auditing module; The user request processing module is used to obtain data usage requests and parse the content to obtain parsed data; The permission and policy management module is used to verify user permissions based on parsed data, and extract the corresponding target data packet and data usage declaration after the verification is successful. The trusted computing processing module is used to perform verifiable computations on the target data packet through a trusted computing node to obtain trusted data and verifiable computation proofs. The blockchain verification module is used to perform compliance verification on verifiable computational proofs based on data usage statements through smart contracts, and obtain verification results. The access control and auditing module is used to grant users access to trusted data when the verification result is passed, generate access audit logs, and store them.

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