NFT and consortium chain-based commodity digital identity verification method and system

Abstract

The embodiment of the application relates to the field of e-commerce, and provides a commodity digital identity verification method and system based on NFT and a consortium chain, which comprises the following steps: based on multi-dimensional state data of commodities in production and circulation processes, generating a unique corresponding NFT digital identity certificate for the commodities on a blockchain smart contract deployed in a consortium chain, and establishing a binding relationship between the NFT digital identity certificate and commodity life cycle data, wherein the consortium chain adopts a chain network architecture of a relay chain and at least one parallel chain; according to the binding relationship, using a national secret algorithm and hash calculation, submitting abstract data of the multi-dimensional state data to a parallel chain for storage and anchoring by the relay chain; constructing commodity circulation data belonging to the circulation process into a data model; based on the data model and the abstract data and cross-chain anchoring results in the consortium chain, performing joint verification, performing consistency judgment on the commodities in the circulation process, and obtaining a final verification result of the commodity digital identity, thereby improving the transparency and security of cross-border e-commerce platforms.

Description

Technical Field

[0001] This application relates to the e-commerce field, and more specifically to a product digital identity verification method and system based on NFT and consortium blockchain. Background Technology

[0002] In the e-commerce sector, digital identity verification of goods has become a core element in ensuring transaction transparency and combating counterfeit and substandard products. However, traditional product traceability systems mainly rely on centralized databases and simple identification technologies (such as barcodes and QR codes), which suffer from technical problems such as data tampering, lack of transparency, and difficulty in verifying authenticity. Especially in cross-border e-commerce platforms, the multi-stage flow of goods from production and logistics to consumption involves multiple parties, and existing technologies cannot effectively solve the problems of data consistency, security, and real-time performance, making it difficult to trace the product traceability chain.

[0003] In existing technologies, product information is typically stored centrally on a single server, with basic tracking relying on static identifiers. On one hand, centralized storage mechanisms lack tamper-proof capabilities, making product information susceptible to malicious modification or forgery (e.g., counterfeit goods can tamper with logistics data to infiltrate the supply chain). Furthermore, they cannot provide a unique, uncopyable digital identity for each product, resulting in a lack of authority in traceability information. On the other hand, dynamic changes in the logistics environment (such as multi-level distribution and cross-border customs clearance) place higher demands on system real-time performance. Existing technologies suffer from high response latency under high-concurrency queries, making it difficult to meet consumers' needs for immediate verification. Moreover, weak data privacy protection mechanisms mean that sensitive information (such as production batches and supplier qualifications) is easily leaked in centralized storage, further weakening system credibility.

[0004] In conclusion, there is an urgent need to propose a new technical solution to address the shortcomings of existing technologies in terms of data integrity, security, and scalability, and to build a highly reliable and transparent digital identity verification system for cross-border e-commerce. Summary of the Invention

[0005] This application provides a product digital identity verification method and system based on NFTs and consortium blockchains. It can acquire and track multi-dimensional status data of products in various stages of production, logistics and sales, realize full lifecycle management of product digital identity, automatically verify product circulation path, node association relationship and time sequence consistency characteristics, and ensure data immutability and traceability through blockchain notarization. It solves the technical problems of existing technologies in terms of data integrity, security and scalability, further protects the authenticity, integrity and circulation compliance of product digital identity, and improves the transparency and security of cross-border e-commerce and supply chain management.

[0006] In a first aspect, embodiments of this application provide a method for digital identity verification of goods based on NFTs and consortium blockchains, the method comprising:

[0007] Based on IoT data acquisition devices, multi-dimensional status data of goods during the production and circulation process is obtained. The multi-dimensional status data includes at least one of the following: product identification information, production information, circulation node information and time series information.

[0008] Based on the multidimensional state data, a unique corresponding NFT digital identity certificate is generated for the product on the blockchain smart contract, and a binding relationship is established between the NFT digital identity certificate and the product's full lifecycle data; wherein the blockchain smart contract is deployed on a consortium blockchain, and the consortium blockchain adopts a chain network architecture that includes a relay chain and at least one parallel chain.

[0009] The multidimensional state data is encrypted using the national cryptographic algorithm according to the binding relationship, and the encrypted data is hashed to obtain digest data; the digest data is submitted to the parachain of the consortium blockchain for notarization, and the notarization result of the parachain is cross-chain anchored through the relay chain;

[0010] The commodity circulation data belonging to the circulation process in the multidimensional state data are associated according to the circulation nodes and time sequence to construct a data model for describing the commodity circulation relationship and time sequence characteristics.

[0011] Based on the data model and the summary data and cross-chain anchoring results in the consortium blockchain, a joint verification is performed to determine the consistency of the circulation path, node association relationship and time sequence consistency characteristics of the goods in the circulation process, and to obtain the final verification result of the digital identity of the goods.

[0012] Secondly, embodiments of this application provide a digital product authentication system based on NFTs and consortium blockchains, which has the function of implementing the digital product authentication method based on NFTs and consortium blockchains provided in the first aspect above. The function can be implemented by hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions, and the modules can be software and / or hardware.

[0013] In one implementation, the NFT-based and consortium blockchain-based digital identity verification system for goods includes:

[0014] The input / output module is configured to acquire multi-dimensional status data of goods during the production and circulation process based on IoT acquisition devices. The multi-dimensional status data includes at least one of the following: goods identification information, production information, circulation node information, and time series information.

[0015] The processing module is configured to generate a unique NFT digital identity credential for the product on a blockchain smart contract based on the multi-dimensional state data, and establish a binding relationship between the NFT digital identity credential and the product's full lifecycle data; wherein the blockchain smart contract is deployed on a consortium blockchain, and the consortium blockchain adopts a chain network architecture including a relay chain and at least one parallel chain; the multi-dimensional state data is encrypted using a national cryptographic algorithm according to the binding relationship, and the encrypted data is hashed to obtain digest data; the digest data is submitted to the parallel chain of the consortium blockchain for notarization, and the notarization result of the parallel chain is cross-chain anchored through the relay chain; the commodity circulation data belonging to the circulation process in the multi-dimensional state data is associated according to the circulation nodes and time sequence to construct a data model for describing the commodity circulation relationship and time sequence characteristics; based on the data model and the digest data in the consortium blockchain and the cross-chain anchoring result, joint verification is performed to determine the consistency of the circulation path, node association relationship and time sequence consistency characteristics of the commodity in the circulation process, and obtain the final verification result of the commodity digital identity.

[0016] Thirdly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a computer, cause the computer to perform the NFT-based and consortium blockchain-based digital authentication method for goods as described in the first aspect.

[0017] Fourthly, embodiments of this application provide a computing device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the NFT-based digital identity verification method for goods based on consortium blockchains as described in the first aspect.

[0018] Fifthly, embodiments of this application provide a computer program product containing instructions that, when run on a computer, cause the computer to execute the NFT and consortium blockchain-based digital identity verification method for goods provided in the first aspect.

[0019] Compared to existing technologies, this application embodiment acquires multi-dimensional state data of goods during production and circulation through IoT data acquisition devices, and generates a unique NFT digital identity certificate for the goods based on the multi-dimensional state data, establishing a binding relationship between the NFT digital identity certificate and the goods' full lifecycle data. Simultaneously, the multi-dimensional state data is encrypted using national cryptographic algorithms and hashed to obtain digest data. The digest data is submitted to a parallel chain of the consortium blockchain for notarization, and the notarization result is cross-chain anchored through a relay chain, thereby achieving tamper-proof and traceability of key data. Furthermore, this application embodiment associates the commodity circulation data during the circulation process according to circulation nodes and time sequence, constructing a data model to describe the commodity circulation relationship and time sequence characteristics. Based on the data model, on-chain digest data, and cross-chain anchoring results, joint verification is performed to determine the consistency of circulation paths, node relationships, and time sequence consistency, outputting the final verification result of the commodity digital identity. This enables automated verification of the authenticity of identity and data integrity throughout the entire cross-border circulation process, improving the transparency and security of cross-border e-commerce and supply chain management, and effectively reducing risks such as substitution, replacement, and fraudulent circulation. Attached Figure Description

[0020] The objectives, features, and advantages of the embodiments of this application will become readily understood by referring to the accompanying drawings and the detailed description of the embodiments. Wherein:

[0021] Figure 1 This is a flowchart illustrating a product digital identity verification method based on NFT and consortium blockchain, according to an embodiment of this application.

[0022] Figure 2 This is a schematic diagram of the structure of a digital identity verification system for goods based on NFT and consortium blockchain, according to an embodiment of this application.

[0023] Figure 3 This is a schematic diagram of the structure of a computing device according to an embodiment of this application. Detailed Implementation

[0024] This application provides a method and system for digital identity verification of goods based on NFTs and consortium blockchains. It can be applied to digital identity management systems in cross-border e-commerce, multi-stage supply chains, and product traceability scenarios. The system may include IoT data acquisition devices, data processing devices, and verification devices. The data processing device and verification device can be deployed integratedly or separately. The data processing device is used to process the collected multi-dimensional state data of goods, including product identification information, production information, circulation node information, and time series information, and to construct a full lifecycle data model of the goods. The verification device is used to verify the digital identity of the goods based on the constructed data model and the summary data in the consortium blockchain, obtaining the product digital identity verification result.

[0025] The data processing device can be an application that performs multi-dimensional state data processing, constructs a full lifecycle data model of goods, and generates NFT digital identity credentials, or a server or terminal device with the above-mentioned application installed; the verification device can be a program that performs a digital identity verification algorithm for goods and makes a consistency judgment on goods circulation data. The program can be calculated based on a discriminant model or deployed on a terminal device for local verification.

[0026] The solutions provided in this application involve technologies such as non-fungible tokens (NFTs), consortium blockchains, artificial intelligence (AI), and computer vision (CV), which are illustrated in the following embodiments:

[0027] NFTs are digital identifiers generated using blockchain technology, possessing uniqueness, non-fungibility, and verifiability. Unlike fungible tokens (such as cryptocurrencies), each NFT corresponds to unique identification information and is logically indivisible or irreplaceable. From a technical perspective, NFTs are typically generated through smart contracts, internally recording metadata associated with a specific object, including but not limited to unique identifiers, attribute descriptions, state information, and related data indexes. NFT ownership, transfer records, and state changes are all recorded through the blockchain, possessing traceable and tamper-proof technical characteristics. In the context of digital identity verification for goods, NFT technology can generate unique digital identity credentials for individual goods or batches of goods, achieving one item, one certificate. NFTs themselves cannot be copied or forged, preventing the reuse of product identities. The generation, binding, and state change records of NFTs can be fully tracked, providing a technical foundation for the entire lifecycle management of goods. Therefore, NFT technology establishes a trustworthy and non-fungible digital identity carrier for goods, providing underlying technical support for verifying product authenticity.

[0028] A consortium blockchain is a type of blockchain technology that falls between public and private blockchains. It features multi-party participation, controlled permissions, and verifiable but not fully public data. Consortium blockchains are typically maintained by multiple organizations or institutions with business relationships, with each participating node participating in data recording and verification according to pre-agreed consensus rules. Consortium blockchains possess core features such as distributed ledgers, consensus mechanisms, encrypted storage, and access control. However, compared to public blockchains, consortium blockchains offer greater controllability and performance advantages in node access, data access, and transaction verification.

[0029] The primary role of consortium blockchain technology in digital product authentication is tamper-proof evidence preservation. Through a distributed ledger structure, it ensures that once a product's key data summary is recorded on the chain, it remains immutable. Multi-party consensus endorsement, with multiple stakeholders including producers, logistics providers, and platforms participating in data verification, enhances data credibility. Access control and privacy protection allow for different levels of data access permissions to different participants, preventing the leakage of sensitive information. Compared to public blockchains, consortium blockchains are more suitable for commercial applications involving high-frequency writes and high-concurrency queries. Through consortium blockchain technology, trusted data collaboration across entities and stages can be achieved while ensuring data authenticity and consistency.

[0030] AI technology is a theoretical, methodological, and technological system that utilizes digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, enabling environmental perception, knowledge acquisition, and decision analysis to achieve optimal processing results. In the embodiments of this application, AI can be used to process complex and ever-changing circulation node data in cross-border e-commerce, intelligently identify abnormal circulation paths and abnormal node dwell conditions, and train a commodity circulation consistency discrimination model through machine learning to achieve high-precision circulation behavior pattern recognition.

[0031] In this embodiment, CV technology can be used to identify physical, non-clonable identity carriers embedded in goods during the production or packaging stage. It acquires the microscopic physical features of the goods through image or optical scanning and converts them into physical identity response values ​​that can be used for NFT digital authentication. The CV processing flow includes feature extraction, perturbation restoration, and target image generation to support subsequent physical authentication and digital identity binding.

[0032] In existing technologies, product information is typically stored centrally in a centralized database, relying on static identifiers (such as barcodes or QR codes) for basic tracking. This approach is easily tampered with and lacks real-time and anti-counterfeiting capabilities. In cross-border, multi-stage circulation, data consistency is difficult to guarantee, and sensitive information is easily leaked under centralized management mechanisms, leading to unreliable product traceability and frequent transaction disputes.

[0033] Compared to existing technologies, this application embodiment achieves tamper-proof, traceable, and dynamic verification of product data by using IoT devices to collect multi-dimensional status data of goods in real time, constructing a full lifecycle data model of goods, generating unique NFT digital identity credentials, and combining this with hash storage via a consortium blockchain. During the circulation process, the data processing device can analyze the product circulation path, node relationships, and dwell time to generate embedded features of the circulation status; the verification device can perform consistency judgment on the circulation data based on a discriminant model, intelligently identify abnormal circulation paths, abnormal node sequences, and abnormal dwell times, and output the final verification result.

[0034] In this embodiment, NFT technology and consortium blockchain technology are combined in a complementary manner. NFTs are used to carry the unique digital identity of goods, realizing the confirmation and identification of goods at the product level; consortium blockchains are used to reliably store and verify the summary information of multi-dimensional state data of goods through multi-party consensus. Through this combination of technologies, the immutable storage and verifiable circulation of product identity information can be achieved without directly disclosing the original sensitive data, thereby constructing a highly reliable digital identity verification system for goods suitable for cross-border e-commerce scenarios.

[0035] It should be noted that the computing devices involved in the embodiments of this application may be servers and / or terminal devices.

[0036] The server involved in the embodiments of this application can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms.

[0037] The terminal devices involved in the embodiments of this application can be devices that provide voice and / or data connectivity to users, handheld devices with wireless connectivity, or other processing devices connected to a wireless modem. Examples include mobile phones (or "cellular" phones) and computers with mobile terminals, such as portable, pocket-sized, handheld, computer-embedded, or vehicle-mounted mobile devices that exchange voice and / or data with a wireless access network. Examples include Personal Communication Service (PCS) phones, cordless phones, Session Initiation Protocol (SIP) phones, Wireless Local Loop (WLL) stations, Personal Digital Assistants (PDAs), and other similar devices.

[0038] Reference Figure 1 , Figure 1 This is a flowchart illustrating a product digital authentication method based on NFTs and consortium blockchains, provided as an embodiment of this application. The method can be executed by a product digital authentication system based on NFTs and consortium blockchains. The method includes steps 101-105:

[0039] Step 101: Acquire multi-dimensional status data of goods during the production and circulation process using IoT data acquisition devices.

[0040] The multidimensional state data includes at least one of the following: product identification information, production information, distribution node information, and time series information.

[0041] Product identification information is the fundamental information used to uniquely identify an individual product or batch of products. Its concept is to establish a non-confusing and non-repeatable identity index for the product. This product identification information may include, but is not limited to, a unique product code, product serial number, batch number, SKU number, manufacturer code, brand identifier, or product model and specifications.

[0042] Product identification information is primarily used to provide a unique identifier for each product or batch of products, preventing confusion or substitution during circulation. It serves as the core index for generating NFT digital identity credentials, achieving a one-to-one correspondence between NFTs and physical products. It also provides the foundational primary key for subsequent multi-source data association, querying, and consistency verification.

[0043] Production information refers to data describing the state of a product during its manufacturing or processing stages. Its concept lies in reflecting the authenticity and compliance of the product's origin and production process. This production information may include production time, production location, production process parameters, production equipment serial numbers, quality inspection results, raw material sources, production batch records, and production environment parameters.

[0044] Production information is primarily used to enable traceability of the origin of goods, preventing counterfeit or unauthorized products from entering the distribution system. It provides data for product quality verification and liability tracing, and, combined with product identification information, constructs a complete lifecycle data chain for goods from their source.

[0045] Distribution node information describes the node status of goods in various stages of logistics, warehousing, and cross-border distribution. Its concept lies in depicting the spatial and node path characteristics of goods within the supply chain network. This distribution node information may include warehousing nodes, transportation nodes, clearance nodes, platform entry nodes, and delivery nodes, with each node corresponding to a node number, node type, geographical location, and operating entity information.

[0046] The circulation node information is used to reconstruct the actual circulation path of goods in cross-border e-commerce scenarios, supporting the determination of whether goods have passed through legitimate nodes and whether they have bypassed key regulatory links. Thus, it provides node-level data support for the circulation consistency verification model.

[0047] Time series information is dynamic data used to describe the temporal sequence and time intervals of goods occurring at various production and distribution nodes. Its concept lies in reflecting the temporal characteristics of the goods circulation process. The time series information may include production completion time, node arrival time, node dwell time, transportation time, customs clearance time, and receipt time, etc.

[0048] Time series information is used to determine whether the circulation of goods conforms to normal logistics time patterns. By analyzing anomalies in time intervals, it identifies whether goods experience abnormal stops, path deviations, or human tampering during circulation. This provides crucial information for verifying the temporal consistency of the goods circulation path.

[0049] For example, step 101 can be achieved through IoT data collection devices. In practical applications, IoT data collection devices may include RFID readers, barcode / QR code scanners, sensors, cameras, or optical scanning devices, used to collect real-time product status information during product production, packaging, warehousing, and logistics transportation. The multi-dimensional status data collected by IoT data collection devices may include the product's unique identifier, production batch, production time, distribution node location, logistics transportation time, storage conditions, environmental information such as temperature and humidity, and other time-series information related to the product's lifecycle. The multi-dimensional status data is transmitted to a data processing device through a data acquisition interface for preliminary cleaning, verification, and formatting to ensure data integrity, accuracy, and traceability.

[0050] Step 102: Based on the multidimensional state data, generate a unique corresponding NFT digital identity certificate for the product on the blockchain smart contract, and establish a binding relationship between the NFT digital identity certificate and the product's full lifecycle data.

[0051] In this embodiment, the NFT digital identity credential refers to a non-fungible digital credential generated based on a blockchain smart contract mechanism, used to uniquely identify the digital identity of a product. The NFT digital identity credential possesses uniqueness, non-replicability, and traceability, and internally includes at least unique identification information for identifying the product's identity and data index information related to the product, serving as the unique carrier of the product's digital identity within the system.

[0052] Product lifecycle data refers to a multi-dimensional set of status data continuously collected and formed throughout the entire process of a single product or batch of products, from production, factory exit, warehousing, logistics and transportation, cross-border customs clearance, platform warehousing, to sales. This product lifecycle data includes at least product production information, distribution node information, and corresponding time-series information, used to comprehensively reflect the product's status changes at different stages.

[0053] The binding relationship refers to the logical association established between NFT digital identity credentials and the corresponding product's full lifecycle data in a product digital identity verification system. This allows the NFT digital identity credentials to be used to uniquely locate and verify the corresponding product's full lifecycle data, thereby ensuring the consistency and traceability between the product's digital identity and the actual product status.

[0054] The blockchain smart contracts are deployed on a consortium blockchain, which employs a network architecture including a relay chain and at least one parallel chain. These smart contracts, deployed on the consortium blockchain, are used to implement on-chain business logic such as the generation (minting / registration), modification (transfer / cancellation), and verification (query / verification) of NFT digital identity credentials, as well as the binding and writing of NFT and product lifecycle data indexes. The consortium blockchain is a permissioned blockchain, jointly maintained by authorized nodes including cross-border e-commerce platforms, manufacturers, logistics and warehousing companies, customs clearance service providers, and testing / regulatory entities. Contract calls are subject to permission control (including role permissions, whitelists, multi-party authorization, or threshold signatures) to ensure the compliance and controllability of data writing and identity operations.

[0055] Furthermore, the consortium blockchain adopts a chain network architecture that includes a relay chain and at least one parallel chain. The parallel chain is used to carry specific business and high-frequency transactions / proof storage. It writes hash digests of multi-dimensional state data, NFT binding relationship digests, and circulation node event digests onto the chain, and can be divided into different parallel chains according to business domains to achieve isolation and expansion.

[0056] The relay chain, acting as a coordination and trusted anchoring layer, is responsible for cross-chain message routing, state confirmation, and finality support between parachains. It also records anchoring information for key parachain results, enabling unified verification of data from different parachains within the consortium blockchain system. Specifically, after a parachain completes its notarization, it uploads the summary or proof of the corresponding block or transaction to the relay chain for cross-chain anchoring. Subsequent verification simultaneously checks both the parachain's notarization results and the relay chain's anchoring records, thereby improving the tamper-resistance, consistency, and traceability of the notarization results and facilitating multi-party collaborative auditing and dispute evidence presentation.

[0057] As an optional embodiment, in step 102, based on the product identification information in the multi-dimensional state data, a unique product identity identifier is generated for the product to be processed through the blockchain smart contract to distinguish different individual products or batches of products; using the product identity identifier as an index, the production information and initial circulation node information corresponding to the product are extracted to generate identity metadata describing the initial state of the product; according to the identity metadata, a corresponding NFT digital identity certificate is generated in the digital identity management system of the cross-border e-commerce platform, and the NFT digital identity certificate is bound one-to-one with the product identity identifier; the circulation node information and time series information collected during the subsequent circulation process of the product are continuously associated with the corresponding NFT digital identity certificate according to the product identity identifier to form the full life cycle data of the product; the identification information of the NFT digital identity certificate and the index relationship of the full life cycle data of the product are stored in the off-chain data system to obtain the binding relationship.

[0058] The generation, transfer, and / or verification transactions of the NFT digital identity credentials are executed on-chain within the consortium blockchain environment, and support settlement of transaction resource consumption through on-chain billing media. Specifically, the cross-border e-commerce platform encapsulates the business logic used for NFT digital identity credential minting and registration, holder changes, status updates, and validity verification into smart contracts deployed on consortium blockchain nodes, which are jointly maintained and executed by approved consortium blockchain member nodes. When an NFT digital identity credential needs to be generated for a product, the digital identity management system calls the smart contract to initiate a minting or registration transaction, writing the NFT identification information and its association information with the product identity identifier and off-chain full lifecycle data index into the on-chain ledger to form a traceable record. When the product undergoes a change of ownership, confirmation by the circulation node, or requires verification during subsequent circulation, transfer and / or verification transactions are initiated by calling the smart contract, respectively. The consortium blockchain consensus mechanism confirms the transaction order and results, thereby ensuring the consistency, non-repudiation, and auditability of the NFT digital identity credential status changes and verification conclusions. Meanwhile, the consortium blockchain sets up a billing mechanism for the computation, storage, and bandwidth consumption of the above-mentioned on-chain transactions. The transaction initiator needs to complete the settlement of resource consumption through the on-chain billing medium in order to achieve quota management and abuse control of on-chain resources, and ensure the sustainability of system operation and service quality.

[0059] Specifically, in the above embodiments, firstly, a unique product identifier is generated for the product to be processed based on the product identification information in the multi-dimensional state data. This product identifier is used to distinguish between different individual products or different product batches, and its generation method can be determined based on the product serial number, production batch number, manufacturer code, or a combination thereof, to ensure uniqueness within the system.

[0060] In this embodiment, the product identification information can be automatically acquired by IoT data acquisition devices during the product production or warehousing stage, including but not limited to product serial number, production batch number, manufacturer code, model code, or combinations thereof. The aforementioned product identification information can be standardized, and corresponding product identifiers can be generated through preset encoding rules or hash mapping rules to ensure uniqueness within the system.

[0061] For example, for goods produced by the same manufacturer in the same production batch, the manufacturer code, production batch number and product serial number can be concatenated to generate a product identification identifier; for goods managed by batch, a batch-level product identification identifier can also be generated based on the production batch number to identify a set of goods in the same batch.

[0062] The above methods enable effective differentiation between different individual products or different batches of products, providing a unified index foundation for subsequent digital identity generation and data association.

[0063] Secondly, using the product identifier as an index, the production information and initial distribution node information corresponding to the product are extracted to generate identity metadata describing the initial state of the product. This identity metadata characterizes the initial state of the product when its digital identity is generated, including but not limited to production entity information, production time information, and initial distribution node information.

[0064] Specifically, based on the product's identity identifier, production information corresponding to the product is retrieved from the production management system or supply chain management system. This includes information on the production entity, production time, production location, and quality inspection. Simultaneously, this information is combined with initial distribution node information collected when the product first enters the distribution process to form identity metadata describing the product's initial state. For example, in a cross-border e-commerce scenario, this initial distribution node information could be the node identifier when the product first enters an export warehouse or domestic distribution center. By integrating the aforementioned production information with the initial distribution node information, identity metadata that comprehensively reflects the product's initial state is generated.

[0065] The identity metadata is used as the basic descriptive information when generating a product's digital identity, ensuring consistency between the product's digital identity and the actual product status.

[0066] Then, based on the identity metadata, an NFT digital identity credential corresponding to the product is generated in the digital identity management system of the cross-border e-commerce platform, and the NFT digital identity credential is bound to the product identity identifier in a one-to-one correspondence.

[0067] In this embodiment, the digital identity management system can generate NFT digital identity credentials based on the identity metadata using a blockchain smart contract mechanism. The NFT digital identity credential includes at least credential identification information for identifying the digital identity of a product and index information pointing to the product's identity identifier.

[0068] For example, during the NFT generation process, the hash value of the product identity identifier can be written into the NFT's metadata field, thereby achieving a unique binding relationship between the NFT digital identity credential and the product identity identifier.

[0069] This method ensures that each NFT digital identity credential corresponds to only one unique product identity identifier, avoiding the problem of the same product being repeatedly generated with multiple digital identities, thereby achieving a unique mapping of product digital identities.

[0070] Subsequently, the circulation node information and time series information collected during the subsequent circulation process of the goods are continuously associated with the corresponding NFT digital identity credential according to the goods' identity identifier, gradually forming the goods' full lifecycle data. The circulation node information may include warehousing nodes, logistics nodes, cross-border clearance nodes, and platform warehousing nodes, etc., and the time series information is used to reflect the temporal sequence of each node.

[0071] In this embodiment, each node in the cross-border circulation process of goods can collect corresponding circulation node information and timestamp information through IoT devices or system interfaces, and record and upload them according to the product identification identifier. Based on the product identification identifier, the above-mentioned circulation node information and time sequence information are continuously written into the data record associated with the corresponding NFT digital identity certificate. For example, when goods enter an overseas warehouse, complete cross-border customs clearance, or enter the platform warehousing stage, the corresponding node identifier and occurrence time can be recorded respectively, and stored in chronological order with the product's NFT digital identity certificate, thereby forming a complete product circulation trajectory.

[0072] By continuously linking data, a complete record of the changes in the state of a product during production and distribution can be achieved, forming full lifecycle data of the product.

[0073] It is understood that the product identification identifier is the core index identifier used in this application embodiment to uniquely distinguish different individual products or product batches. Its essence is a logical index within the system used to associate the product's entire lifecycle data with the NFT digital identity credential, rather than the NFT itself. The product identification identifier generates a 256-bit unique hash value by processing the original product information (such as product serial number, production batch number, manufacturer code, etc.) using the SM3 national cryptographic hash algorithm according to standardized rules, ensuring uniqueness within the system (theoretically, the probability of hash collision is lower than...). As the core index of off-chain data systems (such as MySQL and HBase), the product identity identifier plays a crucial role in identity indexing. Its uniqueness prevents the possibility of multiple uses for the same code, and its logical existence is achieved through hash values, which are not physically present. Functionally, it serves as a data association hub connecting the entire lifecycle data of the product with NFT credentials, and its storage location is strictly limited to the off-chain system. The binding relationship with the NFT digital identity credential (a blockchain credential stored in the consortium blockchain) is achieved through metadata. When the NFT is generated, the hash value of the product identity identifier is written into the metadata field (such as "product_id_hash": "a1b2c3d4"). When consumers verify the data, they use the hash value in the on-chain NFT metadata to locate the entire lifecycle data of the product in the off-chain system in O(1) time, realizing dual verification of on-chain credentials and off-chain data.

[0074] Finally, the identification information of the NFT digital identity certificate and the index relationship of the product's full lifecycle data are stored in the off-chain data system to obtain the binding relationship.

[0075] To balance system performance and storage costs, product lifecycle data can be stored in an off-chain database or distributed storage system, while only the identification information used to identify NFT digital identity credentials and the corresponding data index relationship are recorded. This index relationship is used to quickly locate the product lifecycle data corresponding to the NFT digital identity credential when product digital identity verification is required.

[0076] For example, the mapping relationship between the unique identifier of an NFT digital identity credential and the product identity identifier can be stored in an off-chain system, and the integrity of the off-chain data can be verified subsequently through the digest data stored in the consortium blockchain.

[0077] This step, by storing specific data in an off-chain system and retaining only the index relationship and verification information, not only achieves efficient management of large-scale commodity data, but also provides a reliable data foundation for subsequent digest verification based on consortium blockchain, thereby improving the overall efficiency and security of commodity digital identity verification.

[0078] Through the above embodiments, while ensuring the uniqueness of NFT digital identity credentials, the continuous binding of product digital identity with product lifecycle data is realized. This allows products to be uniformly identified and verified through the same NFT digital identity credentials in all circulation stages of the cross-border e-commerce platform, effectively avoiding the problems of fragmented product identity, data loss or forgery, and providing a reliable data foundation for subsequent circulation consistency verification and identity authenticity judgment.

[0079] Step 103: The multidimensional state data is encrypted using the national cryptographic algorithm according to the binding relationship, and the encrypted data is hashed to obtain digest data; the digest data is submitted to the parachain of the consortium blockchain for notarization, and the notarization result of the parachain is cross-chain anchored through the relay chain.

[0080] The binding relationship is used to limit the access to product lifecycle data through the corresponding NFT digital identity certificate, so as to prevent the mixing or mismatch of data from different products or different batches of products.

[0081] Specifically, in one embodiment of step 103, based on the binding relationship, multi-dimensional state data to be notified is extracted from the product's entire lifecycle data, and the multi-dimensional state data is divided into variable data and immutable data according to data type. Then, the multi-dimensional state data is encrypted using a symmetric or asymmetric encryption algorithm conforming to national cryptographic standards to generate corresponding encrypted data, which is then stored in an off-chain data system. Next, a hash calculation is performed on the encrypted data or the original multi-dimensional state data to generate uniquely corresponding digest data, representing the integrity status of the multi-dimensional state data at a specific time point. Then, the digest data is associated and encapsulated with the corresponding product identity identifier and NFT digital identity credential identification information, and submitted to a parachain of the consortium blockchain for on-chain notarization. The notarization result of the parachain is cross-chain anchored through a relay chain. Finally, the consensus mechanism of the parachain confirms the digest data, and cross-chain consistency verification is achieved by combining the cross-chain anchoring record of the relay chain, thereby realizing the tamper-proof verification and time sequence solidification of the multi-dimensional state data of the product during cross-entity circulation.

[0082] Specifically, firstly, based on the aforementioned binding relationship, multi-dimensional status data to be stored is extracted from the product's entire lifecycle data. This binding relationship restricts access to the product's entire lifecycle data to be indexed only through the corresponding NFT digital identity credential, ensuring data isolation between different products or batches within the system and preventing data commingling or mismatch. In practical implementation, the system can locate the product identity identifier corresponding to the NFT digital identity credential based on its identification information, and then read the corresponding product's multi-dimensional status data from the off-chain data system accordingly.

[0083] For example, when a product enters the cross-border transportation process, the system can extract only the multi-dimensional status data of the product during production, warehousing, and the current logistics node based on the NFT digital identity certificate corresponding to the product, without reading the relevant data of other products.

[0084] Furthermore, the multidimensional state data is divided according to data type to obtain variable data and immutable data. In this embodiment, immutable data may include information such as the product production entity, production time, and initial product identification information, which do not change after the product is generated; variable data may include continuously updated circulation node information, logistics status information, and time series information during the circulation process.

[0085] By classifying and processing multidimensional state data, it is beneficial to adopt differentiated data update and verification strategies for different types of data in the subsequent encryption and evidence preservation process, thereby improving the overall operating efficiency of the system.

[0086] Then, the multidimensional state data is encrypted using a symmetric or asymmetric encryption algorithm conforming to national cryptographic standards to generate corresponding encrypted data, which is then stored in an off-chain data system. In this embodiment, optionally, for large-volume, frequently updated variable data, a national cryptographic symmetric encryption algorithm can be used for encryption. For information used for identification or critical control, a national cryptographic asymmetric encryption algorithm can be used. The encryption key can be uniformly generated and managed by the system key management module to ensure the security and controllability of data access.

[0087] For example, a large amount of logistics node data generated during the cross-border logistics process can be encrypted in batches using symmetric encryption and stored in an off-chain database, while key fields used to identify the product can be encrypted and stored using asymmetric encryption, thereby preventing unauthorized reading or tampering.

[0088] Next, a hash calculation is performed on the encrypted data or the original multidimensional state data to generate a unique corresponding digest data, which characterizes the integrity status of the multidimensional state data at a specific time point.

[0089] In this embodiment, the hash calculation can employ a hash algorithm conforming to national cryptographic standards to calculate the state of the multidimensional state data at the current time node, generating a data digest with a fixed length and unique mapping. The digest data can be used to reflect the integrity characteristics of the corresponding multidimensional state data at the time of generation.

[0090] For example, when a product completes the customs clearance process, a hash calculation is performed on all the multidimensional status data of the product up to the time of customs clearance completion to generate corresponding summary data, which is used to determine whether the data has changed abnormally after that time point.

[0091] Then, the summary data is associated and encapsulated with the corresponding product identity identifier and NFT digital identity credential identifier information, and submitted to the parachain of the consortium blockchain for on-chain notarization. The notarization result of the parachain is then cross-chain anchored through the relay chain. In this embodiment, the system can structurally encapsulate the summary data, product identity identifier, and NFT digital identity credential identifier information to form an on-chain notarization data package, and submit the notarization data package to the consortium blockchain network through the consortium blockchain node interface. For example, the notarization data package can be written to the parachain through the consortium blockchain node interface. After the parachain completes the writing, it generates the corresponding notarization transaction identifier or block height information, and submits the notarization transaction identifier or block summary to the relay chain to form a cross-chain anchoring record.

[0092] For example, after data collection is completed at a certain cross-border logistics node, the system can submit the corresponding summary data, along with the product identification identifier and NFT identification information, to the parachain to record the status snapshot of the product at that node. The relay chain can then anchor the snapshot's evidence storage result for easy cross-chain verification in the future.

[0093] Finally, the consensus mechanism of the parachain is used to verify and confirm the consistency of the digest data. After successful confirmation, the digest data is written into the parachain ledger in the form of blocks, and the cross-chain anchoring record of the relay chain is used to achieve cross-chain verifiability of the evidence storage result. Because the consortium blockchain possesses the characteristics of immutability and temporal ordering, it enables reliable evidence storage of multi-dimensional product state data with the participation of different entities.

[0094] Optionally, nodes in the consortium blockchain can perform consistency verification and confirmation of the digest data using a preset consensus algorithm. After successful confirmation, the digest data is written into the consortium blockchain ledger in the form of blocks. Because the consortium blockchain possesses the characteristics of immutability and temporal ordering, it enables reliable storage of multi-dimensional state data of goods across different stakeholders.

[0095] Through the above steps, it is possible to effectively guarantee the integrity, authenticity, and time sequence consistency of product data throughout its entire lifecycle without directly uploading specific product data to the blockchain. The traceability and verifiability of the evidence storage results are enhanced through the chain network mechanism of parallel chain evidence storage and relay chain anchoring, providing a reliable data foundation for subsequent verification of the consistency of product digital identity.

[0096] Step 104: Associate the commodity circulation data belonging to the circulation process in the multidimensional state data according to the circulation nodes and time sequence to construct a data model for describing the commodity circulation relationship and time sequence characteristics.

[0097] As an optional embodiment, in step 104, the production node, export warehousing node, international transportation node, entry clearance node, platform warehousing node, and consumer delivery node of the goods in the cross-border e-commerce business process are respectively identified as commodity circulation nodes; according to the actual business flow sequence of the goods in the cross-border circulation process, the commodity circulation nodes are sequentially associated to form a cross-border commodity circulation path relationship; corresponding timestamp information is recorded for the circulation relationship between the commodity circulation nodes, and the timestamp information is used to describe the occurrence time and dwell time of the goods in different cross-border links; based on the commodity circulation nodes, the cross-border commodity circulation path relationship, and the timestamp information, a data model for representing the cross-border circulation status of the goods is constructed.

[0098] The above embodiments perform structured modeling of the circulation behavior of goods in the cross-border e-commerce business process to form a data model that can reflect the circulation relationship and time sequence characteristics of goods, providing a foundation for subsequent consistency judgment and compliance verification.

[0099] Specifically, firstly, the key business links in the cross-border e-commerce business process are identified as commodity circulation nodes. In this embodiment, the commodity circulation nodes represent the key locations where the status of goods changes or business handovers occur during the cross-border circulation process. Specifically, the production node, export warehousing node, international transportation node, entry clearance node, platform warehousing node, and consumer delivery node in the cross-border e-commerce business process can be identified as commodity circulation nodes.

[0100] Among them, the production node is used to represent the business link of completing the manufacturing or processing of goods; the export warehousing node is used to represent the warehousing or collection of goods before leaving the country; the international transportation node is used to represent the cross-border transportation stage of goods; the entry clearance node is used to represent the business link of completing customs clearance procedures in the destination country; the platform warehousing node is used to represent the link of goods entering the cross-border e-commerce platform warehousing system; and the consumer delivery node is used to represent the business link of goods finally being delivered to consumers.

[0101] By abstracting the above business processes into nodes, the complex cross-border circulation process can be transformed into a well-structured set of nodes, which facilitates subsequent data association and analysis.

[0102] For example, the circulation nodes of a cross-border e-commerce product may include, in sequence, "domestic production factory", "export warehouse", "international logistics and transportation", "customs clearance in the destination country", "overseas warehouse of the platform", and "consumer signature".

[0103] Furthermore, based on the actual business flow sequence of goods during cross-border circulation, the commodity circulation nodes are systematically associated to form a cross-border commodity circulation path relationship. In this embodiment, the cross-border commodity circulation path relationship is used to describe the order and business dependencies of goods among different circulation nodes. Based on the circulation records generated by the goods at each node, the nodes are sequentially ordered, and path associations between adjacent nodes are established.

[0104] This method allows the cross-border flow of goods to be represented as a clearly directional circulation path, reflecting the complete business flow process from production to final delivery.

[0105] For example, in normal cross-border e-commerce business, the circulation path of goods usually follows the order of "production node → export warehousing node → international transportation node → entry clearance node → platform warehousing node → consumer delivery node", and the corresponding cross-border circulation path relationship is constructed accordingly.

[0106] Next, timestamp information is recorded for the circulation relationship between the commodity circulation nodes.

[0107] In this embodiment, the timestamp information is used to describe the specific time points at which the goods occur in different cross-border stages and the duration of their stay between adjacent nodes. Specifically, the system can record the corresponding node timestamp when the goods arrive at a certain circulation node, and calculate the duration of the goods' stay at that node or in that circulation interval based on the timestamps of adjacent nodes.

[0108] The timestamp information can not only reflect the order of commodity circulation, but also be used to analyze the efficiency characteristics and abnormal situations of commodities in various business links.

[0109] For example, if the dwell time of goods at international transport nodes significantly exceeds the normal range of historical statistics, the anomaly can be identified through the corresponding timestamp information.

[0110] Finally, based on the commodity circulation nodes, the cross-border commodity circulation path relationships, and the timestamp information, a data model is constructed to represent the cross-border commodity circulation status.

[0111] In this embodiment, the data model is used to uniformly describe the spatial relationships (i.e., node and path relationships) and temporal characteristics (i.e., timestamps and dwell time) of goods during cross-border circulation. This data model can be stored in a structured data format, including node sets, node sequence relationships, path relationships between nodes, and corresponding time series characteristics. Therefore, the data model can be used to quantitatively assess the efficiency, compliance, and anomaly risks of cross-border commodity circulation.

[0112] Data models can transform scattered and multi-source circulation data generated during the cross-border circulation of goods into circulation status representations with clear structures and time constraints, thereby providing a unified data foundation for subsequent circulation path analysis, node association judgment, and time sequence consistency verification based on consistency verification models.

[0113] For example, for a certain product, its cross-border circulation status data model can completely record the sequence of each node that the product goes through from production to delivery and the corresponding time information, which can be used to determine whether the product has missing paths, abnormal nodes or abnormal times during subsequent verification.

[0114] Further optionally, in the above embodiments, a data model for representing the cross-border circulation status of goods is constructed based on the commodity circulation nodes, the cross-border circulation path relationships of goods, and the timestamp information, including:

[0115] Each commodity circulation node in the cross-border e-commerce business process is constructed as a node set, and the cross-border circulation path relationship between adjacent commodity circulation nodes is constructed as an edge set. Based on the node set and edge set, a directed acyclic graph structure with unidirectional temporal constraints is formed into a commodity circulation network. Based on the timestamp information, each commodity circulation node in the commodity circulation network is labeled with node timestamp information indicating the time when the commodity arrives at the current node, and each edge in the commodity circulation network is labeled with time interval information indicating the duration of the commodity's stay between adjacent commodity circulation nodes. Based on the node timestamp information and edge time interval information in the commodity circulation network, feature encoding processing is performed on the commodity circulation network to generate a representation of the overall state of cross-border commodity circulation. The data model is constructed by embedding the circulation status features; generating corresponding zero-knowledge proof information based on the circulation status embedding features; verifying whether the cross-border circulation path of goods conforms to preset cross-border circulation compliance rules based on the zero-knowledge proof information; obtaining the zero-knowledge proof verification result; performing time-series alignment analysis between the verified cross-border circulation path of goods and the preset standard cross-border circulation path to calculate the path similarity index reflecting the degree of deviation of the cross-border circulation path of goods; calculating the node anomaly index to characterize the degree of node anomaly based on the difference between the actual dwell time of goods between circulation nodes and the expected dwell time obtained from historical statistics; and weighting and fusing the path similarity index, the node anomaly index, and the zero-knowledge proof verification result to construct the data model. Thus, the data model is used as the input of the commodity circulation consistency verification model for real-time judgment in the commodity digital identity verification process.

[0116] In this embodiment, the various commodity circulation nodes in the cross-border e-commerce business process are first constructed as a node set, and the cross-border circulation path relationships between adjacent commodity circulation nodes are constructed as an edge set. The node set represents the various business nodes that the commodity experiences during the cross-border circulation process, such as production nodes, export warehousing nodes, international transportation nodes, inbound clearance nodes, platform warehousing nodes, and consumer delivery nodes. The edge set represents the flow relationships of the commodity between adjacent nodes.

[0117] Based on the aforementioned set of nodes and edges, a commodity circulation network with a unidirectional temporal constraint is formed. This unidirectional acyclic graph ensures the unidirectionality of the commodity circulation path in the time dimension; that is, commodity circulation can only proceed along the predetermined business direction, and backtracking or cyclical paths are not allowed, structurally avoiding unreasonable combinations of circulation paths.

[0118] For example, for a normal cross-border commodity, its commodity circulation network can be represented as a directed path from a "production node" to a "consumer delivery node", and there is no edge relationship from a subsequent node back to the preceding node.

[0119] Furthermore, based on the timestamp information, each commodity circulation node in the commodity circulation network is labeled with a node timestamp information indicating the time when the commodity arrives at the current node, and each edge in the commodity circulation network is labeled with time interval information indicating the duration of the commodity's stay between adjacent commodity circulation nodes. In this embodiment, the node timestamp information is used to describe the time point when the commodity first arrives at a certain circulation node, and the edge time interval information is used to describe the time consumed by the commodity to complete its circulation between adjacent circulation nodes.

[0120] By time-labeling nodes and edges, the commodity circulation network can be expanded from a simple topological structure into a time-series network with complete temporal information, thus providing a time-dimensional analytical basis for subsequent anomaly detection and consistency judgment.

[0121] For example, if the time interval between the export storage node and the international transportation node is significantly longer than the normal range in historical statistics, it can be reflected as an abnormal edge time feature in the model.

[0122] Furthermore, based on the node timestamp information and edge time interval information in the commodity circulation network, feature encoding processing is performed on the commodity circulation network to generate circulation status embedding features that characterize the overall state of cross-border commodity circulation.

[0123] In this embodiment, the feature encoding process is used to map the structural information and temporal features of the commodity circulation network into a unified vectorized representation, so as to facilitate subsequent automated analysis and model input. The circulation status embedding features can comprehensively reflect the order of commodity circulation paths, node distribution, and temporal change characteristics.

[0124] For example, cross-border circulation networks for different commodities can be encoded into different embedding vectors to distinguish between normal and abnormal circulation states.

[0125] In this embodiment, zero-knowledge proof information is generated based on the embedded features of the circulation status, and the zero-knowledge proof information is used to verify whether the cross-border circulation path of goods complies with the preset cross-border circulation compliance rules.

[0126] The zero-knowledge proof information is used to prove that the cross-border circulation path of goods meets specific compliance conditions without disclosing the specific circulation details of the goods, such as whether it has passed through the necessary clearance points and whether it has followed the prescribed circulation order.

[0127] By introducing a zero-knowledge proof mechanism, it is possible to achieve credible verification of the compliance of cross-border circulation of goods while protecting data privacy, which is suitable for cross-border e-commerce business environments involving multiple parties.

[0128] If the verification is successful, a time-series alignment analysis is performed between the cross-border circulation path of goods and the preset standard cross-border circulation path to calculate the path similarity index, which reflects the degree of deviation of the cross-border circulation path of goods.

[0129] The path similarity index is used to quantify the degree of matching between the actual circulation path of goods and the standard circulation path. When the similarity is low, it indicates that the goods may have missing paths, node jumps, or abnormal detours.

[0130] Simultaneously, based on the difference between the actual dwell time of goods between commodity circulation nodes and the expected dwell time obtained from historical statistics, a node anomaly index is calculated to characterize the degree of abnormal dwell time at each node. This index is used to reflect whether goods are abnormally delayed or abnormally quickly passing through a specific node.

[0131] Finally, the path similarity index, the node anomaly index, and the zero-knowledge proof verification result are weighted and fused to construct the data model. In this embodiment, by using a multi-index fusion approach, the compliance, temporal rationality, and anomaly risk level of the cross-border circulation path of goods can be comprehensively reflected, thereby forming a unified data model for digital identity verification of goods.

[0132] Furthermore, the data model is used as input to the commodity circulation consistency verification model for real-time judgment during the commodity digital identity verification process, enabling the system to reliably judge the authenticity, integrity, and circulation compliance of commodity digital identity during commodity circulation or query verification.

[0133] Optionally, after generating a unique NFT digital identity credential for the product on the blockchain smart contract based on the multi-dimensional state data, the method further includes: acquiring an identity carrier with physically unclonable characteristics embedded in the product during the production or packaging stage; collecting the identity carrier with physically unclonable characteristics embedded in the product during the production or packaging stage before the product is first stored or shipped abroad; converting the physical feature information of the identity carrier into a corresponding physical identity response value through a dynamic response combination conversion function based on a physically unclonable function of optical scattering and an SM3 national cryptographic hash function; binding the physical identity response value with the product's NFT digital identity credential through the blockchain smart contract and recording it in the product's full lifecycle data; collecting the physical feature information of the identity carrier again during cross-border logistics or platform warehousing, and generating a corresponding physical identity response value through the dynamic response combination conversion function; and determining whether the product has been swapped or replaced based on the physical identity response values ​​at different times.

[0134] In this embodiment of the application, the identity carrier refers to a physical identification medium that is embedded in the product itself during the production or packaging stage and has the physical characteristic of being unclonable. Its core feature is the uniqueness and unreplicability of its microscopic physical structure. It is impossible to achieve the same physical characteristics through artificial imitation and is the physical anchor point for binding the physical entity of the product with its digital identity.

[0135] The identity carrier can take various forms, such as photolithographic micro / nano structure tags, randomly textured optical films, and silicone patches with randomly distributed nano-sized particles. The embedding location can be chosen based on the product's attributes, selecting areas that are difficult to disassemble or replace, such as the product itself, packaging seals, or core components. For example, for cross-border cosmetics, micro / nano structure tags can be embedded in the bottle seal, while for cross-border food, randomly textured films can be affixed to the outer packaging seal. The microscopic physical structure of the identity carrier is formed by random physical effects during the production process, and each carrier has unique physical characteristics, providing the underlying physical basis for verifying the uniqueness of the product's physical identity.

[0136] Furthermore, the physical identity response value is used as the verification basis for the uniqueness of the physical entity of the product through the blockchain smart contract, and is matched and compared with the physical identity response values ​​in the historical records. When the matching results between physical identity response values ​​generated at different times meet the preset consistency threshold condition, it is determined that the product has not been swapped or replaced. When the matching results between physical identity response values ​​generated at different times do not meet the preset consistency threshold condition, it is determined that the product has an abnormal risk.

[0137] The dynamic response combination conversion function based on optical scattering-based Physical Unclonable Function (PUF) and SM3 national cryptographic hash function refers to a hybrid conversion function constructed by combining the dynamic physical response characteristics of the PUF with the cryptographic hash characteristics of the SM3 national cryptographic hash function. In this embodiment, the dynamic response combination conversion function based on optical scattering-based PUF and SM3 national cryptographic hash function is used to convert the physical feature information of the identity carrier into a stable, comparable, and secure digital response result.

[0138] Building upon the physically unclonable function's response generation mechanism, the dynamic response combination transformation function introduces random challenge parameters and a time factor, and combines this with the SM3 national cryptographic hash function for secondary mapping, thereby generating a digital identity response value associated with the collection time and challenge parameters. Through the dynamic response combination transformation function, the uniqueness advantage of the physically unclonable function is preserved, while further enhancing the response results' resistance to replay and counterfeiting.

[0139] Optionally, in the above steps, the physical feature information of the identity carrier is converted into a corresponding physical identity response value through a dynamic response combination conversion function based on the physical non-cloning function of optical scattering and the SM3 national cryptographic hash function. This includes: scanning the identity carrier embedded in the product using an optical acquisition device to obtain an optical scattering response signal; preprocessing the optical scattering response signal to extract the microscopic physical structure features of the identity carrier; combining random challenge parameters to perform dynamic response mapping processing based on the physical non-cloning function on the microscopic physical structure features to generate first intermediate response data; wherein the random challenge parameters include at least on-chain challenge parameters generated from on-chain data of the consortium blockchain; and inputting the first intermediate response data into the SM3 national cryptographic hash function for hash calculation to generate a physical identity response value associated with the acquisition time of the optical acquisition device and the random challenge parameters.

[0140] The physical identity response value refers to the digital response result obtained after converting the physical feature information of the identity carrier through the dynamic response combination conversion function. The physical identity response value has the following characteristics: the response values ​​generated by the identity carrier of the same product under the same challenge parameters are highly consistent; even if the identity carriers of different products are similar in appearance, their generated physical identity response values ​​will show significant differences; and the consistency of the physical entity of the product can be verified by matching and comparing it with historical response values.

[0141] In this embodiment, the physical identity response value is used as the verification basis for the uniqueness of the physical entity of the product, and it is bound to the corresponding NFT digital identity certificate of the product and recorded in the product's full lifecycle data. For example, the physical identity response value generated when the product is first put into storage can be used as a baseline value. New response values ​​collected again in subsequent cross-border logistics or platform warehousing stages can be matched with the baseline value to determine whether the product has been swapped or replaced.

[0142] Specifically, the step of converting the physical characteristic information of the identity carrier into a corresponding physical identity response value can be implemented as follows: First, the identity carrier embedded in the product is scanned using an optical acquisition device to obtain an optical scattering response signal. The optical acquisition device may include a laser light source, an optical sensor, and an image acquisition module, used to emit a beam of light of a specific wavelength onto the identity carrier and acquire the scattering pattern formed under the influence of its microstructure. Due to the randomness of the microstructure within the identity carrier, the optical scattering response signals formed by different identity carriers under the same illumination conditions exhibit significant differences.

[0143] Furthermore, the optical scattering response signal is preprocessed to extract the microscopic physical structure features of the identity carrier. In this embodiment, the preprocessing may include operations such as denoising, normalization, and feature enhancement to eliminate the influence of ambient light interference or acquisition errors. Subsequently, stable feature representations, such as scattering intensity distribution features, frequency domain features, or texture features, are extracted from the processed optical scattering response signal. In this way, the complex optical scattering signal is transformed into physical feature data that can be used for subsequent calculations.

[0144] Furthermore, by incorporating random challenge parameters, dynamic response mapping processing based on a physically non-cloning function is performed on the microscopic physical structure features to generate first intermediate response data. The random challenge parameters are random variables dynamically generated by the system during each acquisition or verification, used to modify the input conditions of the physically non-cloning function. For example, the random challenge parameters may include the light source incident angle, light intensity modulation parameters, random seed values, or combinations thereof.

[0145] By introducing random challenge parameters, the response results generated by the same identity carrier at different times have dynamic change characteristics, thereby effectively preventing attackers from performing replay attacks by copying historical response values.

[0146] The first intermediate response data refers to the preliminary response result obtained after mapping based on the microscopic physical structure characteristics and random challenge parameters using a physically non-cloning function. This first intermediate response data still retains the joint information of the physical characteristics and challenge parameters, but has not yet undergone secure hashing.

[0147] Finally, the first intermediate response data is input into the SM3 national cryptographic hash function for hash calculation to generate a physical identity response value associated with the acquisition time of the optical acquisition device and the random challenge parameters.

[0148] In this embodiment, the SM3 national cryptographic hash function is used to map the first intermediate response data into a fixed-length digest value, thereby achieving standardized representation and security protection of physical identity information. Through this step, the final physical identity response value used for storage, binding, and comparison can be obtained.

[0149] In this embodiment, the physical identity response values ​​generated at different times are matched and compared to determine whether the goods have been swapped or replaced.

[0150] Specifically, the physical identity response value generated at the current moment is compared with the physical identity response values ​​in the historical records. When the comparison result meets the preset consistency threshold condition, it is determined that the physical entity of the product remains consistent and no substitution or swapping has occurred. When the comparison result does not meet the preset consistency threshold condition, it is determined that the product has an abnormal risk, and the corresponding abnormal identification information can be included in the product's digital identity verification conclusion. By combining the physical non-clonable identity verification mechanism with the NFT digital identity and consortium blockchain evidence storage mechanism, this application embodiment achieves strong binding verification between the product's digital identity and physical entity, effectively improving the reliability of product anti-counterfeiting, anti-swapping, and traceability verification in cross-border e-commerce scenarios.

[0151] Step 105: Based on the data model and the summary data and cross-chain anchoring results in the consortium blockchain, a joint verification is performed to determine the consistency of the circulation path, node relationships, and time sequence consistency characteristics of the goods during the circulation process, thus obtaining the final verification result of the goods' digital identity. The final verification result is used to determine the authenticity, integrity, and compliance of the goods' digital identity in the cross-border circulation process, supporting the business needs of cross-border e-commerce platforms for product anti-counterfeiting traceability, compliance review, and risk warning.

[0152] As an optional embodiment, in step 105, based on the data model, the circulation path, node relationships, and time sequence consistency characteristics of the goods during the circulation process are analyzed to establish a goods circulation consistency verification model. During the goods digital identity verification process, based on the goods circulation consistency verification model, the consistency judgment of the goods circulation data associated with the NFT digital identity certificate is performed, and the corresponding consistency judgment result is output. The consistency judgment result is verified by combining the digest data in the consortium blockchain and the cross-chain anchoring result formed through the relay chain, to obtain the final verification result of the goods digital identity. Further optionally, the consistency judgment result and / or the final verification result are hashed to obtain result digest data, and the result digest data is submitted to the consortium blockchain's parachain for storage, and cross-chain anchoring is performed through the relay chain.

[0153] First, based on the data model, the circulation path, node relationships, and time sequence consistency characteristics of goods in the circulation process are analyzed to establish a commodity circulation consistency verification model.

[0154] Optionally, in this embodiment, commodity circulation data samples verified to be in normal circulation status and whose corresponding summary data has been stored on the consortium blockchain's parallel chain and completed cross-chain anchoring are extracted from the data model, serving as a training sample set for normal commodity circulation behavior. Based on the training sample set, the path sequence characteristics, node association characteristics, and time-series change characteristics of commodities between different commodity circulation nodes are jointly modeled to generate feature representations characterizing normal commodity circulation behavior patterns. Based on these feature representations, a discriminant model is constructed to describe the consistency of cross-border commodity circulation behavior, enabling the discriminant model to quantitatively evaluate the deviation between the actual circulation status of commodities and normal circulation behavior patterns. Historical abnormal circulation samples or rule-based abnormal circulation samples are used to perform comparative learning or supervised optimization on the discriminant model, so that the discriminant model has the ability to identify abnormal circulation paths, abnormal node sequences, and abnormal dwell times. Optionally, the model parameters and / or model version information after training of the discrimination model are hashed to obtain model summary data. The model summary data is then submitted to the parachain of the consortium blockchain for storage and cross-chain anchoring through the relay chain to verify the traceability of the model's source and version.

[0155] In this embodiment, the data model already includes a set of nodes for cross-border commodity circulation, ordered path relationships between nodes, arrival times of each node, and dwell times between nodes. Therefore, the following core feature dimensions can be directly extracted from this data model: path sequence features, used to describe whether the commodity passes through each commodity circulation node in the expected cross-border business process order; node association features, used to describe whether the connection relationship between adjacent commodity circulation nodes conforms to business logic constraints; and temporal consistency features, used to describe whether the time distribution and dwell time of the commodity between circulation nodes are within a reasonable range. By jointly analyzing the above features, a foundation is provided for subsequently constructing a commodity circulation consistency verification model.

[0156] Furthermore, commodity circulation data samples verified to be in normal circulation status and whose corresponding summary data has been stored on the consortium blockchain parachain and completed cross-chain anchoring are extracted from the data model and used as training sample sets for normal commodity circulation behavior. The normal circulation status can be determined by historical manual review results, order records that have completed compliant customs clearance, or commodity circulation records confirmed by the cross-border platform to be without anomalies. Each sample is associated with a corresponding commodity identity identifier and / or NFT digital identity credential. For example, for a certain cross-border commodity, its historical circulation path sequentially passes through "production node—export warehousing node—international transportation node—entry clearance node—platform warehousing node—consumer delivery node," and the dwell time at each node is within the statistically normal range. Therefore, the commodity's circulation data can be marked as a normal sample and included in the training sample set. Simultaneously, the commodity's notified transaction identifier on the parachain and relay chain anchoring information are retained for sample traceability verification.

[0157] Next, based on the training sample set, the path sequence features, node association features, and temporal change features of goods between different commodity circulation nodes are jointly modeled to generate a feature representation for characterizing the normal circulation behavior pattern of goods. In this embodiment, the feature representation can be in the form of a multi-dimensional vector, used to comprehensively depict the typical circulation behavior characteristics of goods in the cross-border circulation process. For example, the feature representation can simultaneously reflect whether the goods exhibit node skipping, path backtracking, or abnormal dwell time.

[0158] By modeling a large number of normal circulation samples, a benchmark for normal circulation behavior patterns with statistical stability is formed.

[0159] Then, based on the feature representation, a discriminant model is constructed to describe the consistency of cross-border commodity circulation behavior, enabling the discriminant model to quantitatively assess the degree of deviation between the actual circulation status of commodities and normal circulation behavior patterns. In this embodiment, the discriminant model can be a machine learning-based or rule-fusion-based discriminant model, used to output an assessment result reflecting the degree of consistency in commodity circulation.

[0160] Furthermore, the discrimination model is subjected to comparative learning or supervised optimization using historical abnormal flow samples or rule-based abnormal flow samples, so that the discrimination model has the ability to identify the following abnormal situations: abnormal flow paths, such as missing clearance points or bypassing platform warehousing nodes; abnormal node order, such as clearing customs before international transportation; abnormal dwell time, such as dwell time at a certain logistics node significantly exceeding the historical statistical range.

[0161] Through the above training and optimization process, the commodity circulation consistency verification model can effectively distinguish between normal circulation behavior and abnormal circulation behavior.

[0162] Furthermore, during the product digital identity verification process, based on the product circulation consistency verification model, the consistency of product circulation data associated with the NFT digital identity credential is assessed, and the corresponding consistency assessment result is output. For example, when the actual circulation path sequence of a product is consistent with the normal circulation behavior pattern, and the deviation of node dwell time is within the allowable range, the consistency assessment result can be marked as "passed". When an abnormal path sequence or abnormal dwell time of multiple nodes is detected, the consistency assessment result can be marked as "risk exists".

[0163] Optionally, in this embodiment, based on the commodity circulation data associated with the NFT digital identity credential, the actual circulation path of the commodity in the cross-border circulation process is compared and analyzed with a preset standard cross-border circulation path to obtain a path consistency analysis result for characterizing path consistency. Based on the node timestamp information of each commodity circulation node and the time interval information between adjacent nodes in the commodity circulation data, the temporal change characteristics of the commodity between each commodity circulation node are analyzed to obtain a temporal consistency analysis result for characterizing temporal consistency. The path consistency analysis result and the temporal consistency analysis result are input into the commodity circulation consistency verification model for joint discrimination, and a consistency judgment result for characterizing whether the commodity circulation status conforms to the normal circulation behavior pattern is output.

[0164] Specifically, multi-dimensional status data and timestamp information collected at various circulation nodes (such as production, warehousing, international transportation, customs clearance, and platform warehousing) are input into the commodity circulation consistency verification model. The consistency analysis model compares the actual circulation path of the commodity with historical normal circulation patterns or preset standard cross-border circulation paths, analyzes whether the node sequence meets expectations, and calculates the path consistency score. Based on the timestamp information of commodity circulation nodes and the dwell time between adjacent nodes, it analyzes whether the actual circulation time sequence matches the expected time sequence, obtaining a time sequence consistency index. The path consistency analysis results and the time sequence consistency analysis results are input into the verification model for joint judgment, outputting a consistency judgment result reflecting whether the commodity circulation status conforms to the normal circulation behavior pattern, such as "conforms" or "does not conform".

[0165] For example, suppose the standard distribution path for a cross-border commodity is: production—export warehousing—international transportation—import customs clearance—platform warehousing—consumer delivery. If the "import customs clearance" node is skipped in the actual distribution path, the path consistency analysis result will show a deviation from the standard path, and the time sequence consistency analysis may show an abnormal dwell time at a certain logistics node, thus jointly determining and outputting a consistency judgment result of "non-compliant".

[0166] Optionally, during the product digital identity verification process, after performing a consistency judgment on the product circulation data associated with the NFT digital identity credential based on the product circulation consistency verification model and outputting the corresponding consistency judgment result, the process further includes: based on the consistency judgment result, detecting whether there are abnormal product circulation node jumps, abnormal time intervals, or deviations in product circulation paths at international transportation nodes, entry clearance nodes, or cross-border e-commerce platform warehousing nodes; when abnormal circulation conditions are detected, generating abnormal identification information corresponding to the abnormal type, the abnormal identification information being used to characterize the abnormal circulation state of the product at the corresponding circulation stage; associating the abnormal identification information with the consistency judgment result and incorporating it as a verification basis into the final verification result of the product digital identity, so as to determine the authenticity, integrity, and circulation compliance of the product digital identity.

[0167] This embodiment can monitor abnormal circulation of goods at key cross-border nodes (such as international transportation nodes, entry clearance nodes, and platform warehousing nodes). Specifically, based on the consistency determination results, the system analyzes the circulation of goods at international transportation nodes, entry clearance nodes, and cross-border e-commerce platform warehousing nodes to determine if there are any abnormal product circulation node jumps, abnormal time intervals, or deviations in product circulation paths.

[0168] During the detection of node jumps in the commodity circulation process, the system compares the actual sequence of nodes traversed by the commodity with a preset standard cross-border circulation path. When there are omissions, repetitions, or abnormal sequences of nodes in the actual circulation path, it is determined to be a node jump anomaly. For example, if the standard path is "production—export warehousing—international transportation—import customs clearance—platform warehousing", but the "import customs clearance" node is skipped in the actual path, the system will identify the node jump anomaly.

[0169] During the abnormal time interval detection process, based on the node timestamp information in the commodity circulation data and the dwell time between adjacent nodes, historical statistics or preset thresholds are compared to identify abnormal situations where the dwell time at a certain node is too long or too short. For example, if the actual dwell time of a commodity at an international transportation node exceeds twice the historical average dwell time, it is determined to be an abnormal time interval.

[0170] In the process of detecting deviations in the commodity distribution path, the degree of deviation is quantified by comparing the similarity between the actual distribution path and the preset standard path. When the path similarity is lower than a set threshold, the system determines that the commodity has an abnormal path deviation. For example, if a commodity goes directly to the platform's warehouse after being stored in an export warehouse without going through international transportation or entry clearance points, it is identified as having an abnormal path deviation.

[0171] When any of the above-mentioned abnormal circulation situations is detected, an anomaly identification information corresponding to the anomaly type will be generated to characterize the abnormal state of the goods at the corresponding circulation stage. Examples include "international transport delay anomaly," "customs clearance skipping anomaly," or "cross-border route deviation anomaly." This anomaly identification information is then correlated with the aforementioned consistency judgment results to form comprehensive verification information describing the circulation status of the goods.

[0172] Finally, the anomaly identification information and consistency judgment results are used as verification criteria and incorporated into the final verification result of the product's digital identity. This method not only determines the consistency of product circulation during the digital identity verification process but also identifies potential risks such as tampering, replacement, or abnormal retention in real time, thereby providing a reliable judgment on the authenticity, integrity, and compliance of product circulation.

[0173] For example, if a cross-border e-commerce product fails to pass through the entry clearance checkpoint during transportation and stays in the platform's warehousing node for an abnormally long time, the system will detect the node jump anomaly and the time interval anomaly, and generate corresponding anomaly identification information "entry clearance skipped anomaly" and "platform warehousing delay anomaly". After associating these with the consistency judgment result "partial non-compliance", the final verification result is "digital identity has an abnormal risk", prompting the cross-border e-commerce platform or regulator to conduct further verification.

[0174] For example, if a product's transit time in the international shipping process is significantly longer than twice the historical average, an anomaly flag "International Shipping Delay Anomaly" can be generated. This information, along with the consistency judgment result "Partial Non-compliance," can be included in the final verification result to alert cross-border e-commerce platforms to the potential risks of the product.

[0175] Finally, by combining the summary data in the consortium blockchain and the cross-chain anchoring results formed through the relay chain, the consistency judgment result is verified to obtain the final verification result of the commodity digital identity. In this embodiment, the summary data is a data summary obtained by encrypting the key node data of commodity circulation off-chain or by hashing it at the current time point, and is written into the parachain as a proof carrier. At the same time, the relay chain performs cross-chain anchoring on the corresponding proof transaction summary or block summary to ensure the immutability, temporal order, and traceability of commodity circulation data throughout its entire lifecycle. During the verification phase, the commodity circulation data summary used in the consistency judgment process is compared with the summary data already stored in the parachain, and the anchoring record of the proof result on the relay chain is further verified to see if it matches. This verifies whether the data on which the consistency judgment is based is authentic, its content has not been tampered with, and it has cross-chain verifiability.

[0176] When the consistency determination result meets the preset consistency threshold, and the hash digest of the consistency determination basis data used for verification is consistent with the digest data already stored in the consortium blockchain parallel chain, and the cross-chain anchoring record corresponding to the relay chain passes verification, the final verification result of the product digital identity is output as genuine and compliant. When any of the above verifications fails, a risk identifier or anomaly determination result corresponding to the failed step is output. The risk identifier includes at least data digest inconsistency, cross-chain anchoring verification failure, path deviation exceeding the threshold, and / or abnormal node dwell time sequence.

[0177] In this embodiment, a scheme that involves real-time collection of multi-dimensional product status data, construction of a full product lifecycle data model, generation of NFT digital identity credentials, and hash storage on a consortium blockchain enables end-to-end traceability and tamper-proof verification of cross-border product circulation. The resulting digital identity verification results can accurately determine the authenticity, integrity, and compliance of product circulation, thereby reducing the risk of counterfeit and substandard goods circulation, providing users with a better cross-border shopping experience, and reducing transaction disputes caused by information asymmetry.

[0178] The above describes a product digital identity verification method based on NFT and consortium blockchain in the embodiments of this application. The following describes a product digital identity verification system based on NFT and consortium blockchain that implements the above product digital identity verification method based on NFT and consortium blockchain.

[0179] See Figure 2 ,like Figure 2 The diagram shows a structural schematic of a digital product authentication system based on NFTs and a consortium blockchain. The digital product authentication system based on NFTs and a consortium blockchain in this embodiment can achieve the aforementioned... Figure 1 The steps of the NFT-based and consortium blockchain-based digital product authentication method are executed in the corresponding embodiments. The functions of the NFT-based and consortium blockchain-based digital product authentication system can be implemented in hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions, and the modules can be software and / or hardware. The NFT-based and consortium blockchain-based digital product authentication system may include an input / output module 201 and a processing module 202. The functional implementation of the processing module 202 and the input / output module 201 can be found in [reference needed]. Figure 1 The operations performed in the corresponding embodiments will not be described in detail here. For example, the processing module 202 can be used to control the sending, receiving, and acquiring operations of the input / output module 201.

[0180] The input / output module 201 is configured to acquire multi-dimensional status data of goods during the production and circulation process based on IoT acquisition devices. The multi-dimensional status data includes at least one of the following: goods identification information, production information, circulation node information, and time series information.

[0181] The processing module 202 is configured to generate a unique NFT digital identity credential for the product on a blockchain smart contract based on the multi-dimensional state data, and establish a binding relationship between the NFT digital identity credential and the product's full lifecycle data; wherein the blockchain smart contract is deployed on a consortium blockchain, and the consortium blockchain adopts a chain network architecture including a relay chain and at least one parallel chain; the multi-dimensional state data is encrypted using a national cryptographic algorithm according to the binding relationship, and the encrypted data is hashed to obtain digest data; the digest data is submitted to the parallel chain of the consortium blockchain for notarization, and the notarization result of the parallel chain is cross-chain anchored through the relay chain; the commodity circulation data belonging to the circulation process in the multi-dimensional state data is associated according to the circulation nodes and time sequence to construct a data model for describing the commodity circulation relationship and time sequence characteristics; based on the data model and the digest data in the consortium blockchain and the cross-chain anchoring result, joint verification is performed to judge the consistency of the circulation path, node association relationship and time sequence consistency characteristics of the commodity in the circulation process, and obtain the final verification result of the commodity digital identity.

[0182] In this embodiment, the processing module 202 binds multi-dimensional product status data one-to-one with NFT digital identity credentials, and combines national cryptographic encryption processing with a consortium blockchain evidence storage scheme to achieve unique identification, tamper-proof recording, and real-time verification of cross-border product circulation information. This results in a final verification result that accurately reflects the authenticity, integrity, and compliance of the product's digital identity. This solution reduces the risk of inaccurate digital identity verification caused by centralized database tampering, information silos, or anomalies in cross-border circulation, providing users with immediate and reliable product digital identity verification services, thus leading to a better user experience and reducing disputes and losses caused by counterfeiting, substitution, or information inconsistencies.

[0183] In short, in this embodiment of the application, the digital identity management and verification scheme that combines NFTs and consortium blockchains, implemented by the processing module 202, enables each product to have a unique and verifiable digital identity in the production, logistics and sales processes. At the same time, the encryption and evidence storage mechanisms ensure data security and immutability, providing highly reliable product traceability and compliance verification services for cross-border e-commerce and consumers.

[0184] The above describes the NFT-based and consortium blockchain-based digital product authentication system 20 in this application embodiment from the perspective of modular functional entities. The following describes the NFT-based and consortium blockchain-based digital product authentication system in this application embodiment from the perspective of hardware processing.

[0185] It should be noted that, Figure 2 The physical device corresponding to the input / output module 201 shown can be a transceiver, radio frequency circuit, communication module, and input / output (I / O) interface, etc., and the physical device corresponding to the processing module 202 can be a processor.

[0186] Figure 2 All of the above can have the following characteristics: Figure 3 The structure shown, when Figure 2 The NFT-based and consortium blockchain-based digital identity verification system 20 shown has the following characteristics: Figure 3 When the structure shown is used, Figure 3 The processor and transceiver in the device can perform the same or similar functions as the processing module 202 and input / output module 201 provided in the aforementioned device embodiments. Figure 3 The memory storage processor in the memory needs to call the computer program when executing the above-mentioned NFT and consortium blockchain-based digital authentication method for goods.

[0187] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0188] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0189] In the embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, apparatuses, or modules, and may be electrical, mechanical, or other forms.

[0190] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0191] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium.

[0192] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product.

[0193] The computer program product includes one or more computer instructions. When the computer program is 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 may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may 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 may be any available medium that a computer can store or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., a solid-state disk (SSD)).

[0194] The technical solutions provided in the embodiments of this application have been described in detail above. Specific examples have been used in the embodiments of this application to illustrate the principles and implementation methods of the embodiments of this application. The description of the above embodiments is only for the purpose of helping to understand the methods and core ideas of the embodiments of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the embodiments of this application. Therefore, the content of this specification should not be construed as a limitation on the embodiments of this application.

Claims

1. A method for digital identity verification of goods based on NFTs and consortium blockchains, characterized in that, The method includes: Based on IoT data acquisition devices, multi-dimensional status data of goods during the production and circulation process is obtained. The multi-dimensional status data includes at least one of the following: product identification information, production information, circulation node information and time series information. Based on the multidimensional state data, a unique corresponding NFT digital identity certificate is generated for the product on the blockchain smart contract, and a binding relationship is established between the NFT digital identity certificate and the product's full lifecycle data; wherein the blockchain smart contract is deployed on a consortium blockchain, and the consortium blockchain adopts a chain network architecture that includes a relay chain and at least one parallel chain. The multidimensional state data is encrypted using the national cryptographic algorithm according to the binding relationship, and the encrypted data is hashed to obtain digest data; the digest data is submitted to the parachain of the consortium blockchain for notarization, and the notarization result of the parachain is cross-chain anchored through the relay chain; The commodity circulation data belonging to the circulation process in the multidimensional state data are associated according to the circulation nodes and time sequence to construct a data model for describing the commodity circulation relationship and time sequence characteristics. Based on the data model and the summary data and cross-chain anchoring results in the consortium blockchain, a joint verification is performed to determine the consistency of the circulation path, node association relationship and time sequence consistency characteristics of the goods in the circulation process, and to obtain the final verification result of the digital identity of the goods.

2. The product digital identity verification method based on NFT and consortium blockchain according to claim 1, characterized in that, Based on the multi-dimensional state data, the process of generating a unique NFT digital identity credential for the product on a blockchain smart contract and establishing a binding relationship between the NFT digital identity credential and the product's full lifecycle data includes: Based on the product identification information in the multidimensional state data, a unique product identity identifier is generated for the product to be processed through the blockchain smart contract, which is used to distinguish different individual products or batches of products. Using the product identifier as an index, extract the production information and initial circulation node information corresponding to the product to generate identity metadata describing the initial state of the product; Based on the identity metadata, a corresponding NFT digital identity certificate is generated in the digital identity management system of the cross-border e-commerce platform, and the NFT digital identity certificate is bound one-to-one with the product identity identifier; the generation, transfer and / or verification of the NFT digital identity certificate are executed in the on-chain environment of the consortium blockchain, and the settlement of transaction resource consumption completed through the on-chain billing medium is supported. The circulation node information and time series information collected during the subsequent circulation process of the product are continuously associated with the corresponding NFT digital identity certificate according to the product identity identifier, thus forming the product's full life cycle data; The binding relationship is obtained by storing the identification information of the NFT digital identity certificate and the index relationship of the product's full lifecycle data in an off-chain data system.

3. The product digital identity verification method based on NFT and consortium blockchain according to claim 1, characterized in that, The step of associating commodity circulation data belonging to the circulation process in the multidimensional state data according to circulation nodes and time sequence to construct a data model for describing commodity circulation relationships and time sequence characteristics includes: The production node, export warehousing node, international transportation node, entry clearance node, platform warehousing node, and consumer delivery node of goods in the cross-border e-commerce business process are respectively identified as commodity circulation nodes. Based on the actual business flow sequence of goods in the cross-border circulation process, the commodity circulation nodes are systematically associated to form a cross-border commodity circulation path relationship; The timestamp information is recorded for the circulation relationship between the commodity circulation nodes. The timestamp information is used to describe the occurrence time and duration of the commodity in different cross-border links. Based on the commodity circulation nodes, the cross-border commodity circulation path relationships, and the timestamp information, a data model is constructed to represent the cross-border circulation status of commodities.

4. The product digital identity verification method based on NFT and consortium blockchain according to claim 3, characterized in that, The step of constructing a data model to represent the status of cross-border commodity circulation based on the commodity circulation nodes, the cross-border commodity circulation path relationships, and the timestamp information includes: Each commodity circulation node in the cross-border e-commerce business process is constructed as a node set, and the cross-border circulation path relationship between adjacent commodity circulation nodes is constructed as an edge set. Based on the set of nodes and the set of edges, a commodity circulation network with a directed acyclic graph structure and unidirectional temporal constraints is formed. Based on the timestamp information, each commodity circulation node in the commodity circulation network is labeled with node timestamp information to indicate the time when the commodity arrives at the current node, and each side of the commodity circulation network is labeled with time interval information to indicate the duration of the commodity stay between adjacent commodity circulation nodes; Based on the node timestamp information and edge time interval information in the commodity circulation network, feature encoding processing is performed on the commodity circulation network to generate circulation status embedding features that characterize the overall state of cross-border commodity circulation. Based on the embedded features of the circulation status, corresponding zero-knowledge proof information is generated. Based on the zero-knowledge proof information, it is verified whether the cross-border circulation path of the goods complies with the preset cross-border circulation compliance rules, and the zero-knowledge proof verification result is obtained. The verified cross-border circulation routes of goods are aligned with the preset standard cross-border circulation routes in a time series analysis, and a path similarity index reflecting the degree of deviation of the cross-border circulation routes of goods is calculated. Based on the difference between the actual dwell time of goods between commodity circulation nodes and the expected dwell time obtained from historical statistics, a node anomaly index is calculated to characterize the degree of node dwell anomaly. The path similarity index, the node anomaly index, and the zero-knowledge proof verification result are weighted and fused to construct the data model.

5. The product digital identity verification method based on NFT and consortium blockchain according to claim 1, characterized in that, After generating a unique NFT digital identity credential for the product on the blockchain smart contract based on the multi-dimensional state data, the process further includes: To obtain a physically unclonable identity carrier embedded in a product during the production or packaging stage; Before goods are first stored or exported, collect the identity carriers that have physical non-clonable characteristics embedded in the goods during the production or packaging stage; The physical characteristic information of the identity carrier is converted into the corresponding physical identity response value by a dynamic response combination conversion function based on the physical non-cloning function of optical scattering and the SM3 national cryptographic hash function. The physical identity response value is bound to the product's NFT digital identity credential through the blockchain smart contract and recorded in the product's full lifecycle data; The physical characteristic information of the identity carrier is collected again in the cross-border logistics or platform warehousing process, and the corresponding physical identity response value is generated through the dynamic response combination conversion function. By analyzing the physical identity response values ​​at different times, it can be determined whether the goods have been swapped or replaced.

6. The product digital identity verification method based on NFT and consortium blockchain according to claim 5, characterized in that, The process of converting the physical feature information of the identity carrier into a corresponding physical identity response value through a dynamic response combination conversion function based on the physically unclonable function of optical scattering and the SM3 national cryptographic hash function includes: The identification carrier embedded in the product is scanned using an optical acquisition device to obtain the optical scattering response signal; The optical scattering response signal is preprocessed to extract the microscopic physical structure features of the identity carrier; By combining random challenge parameters, dynamic response mapping processing based on a physically non-cloning function is performed on the microscopic physical structure features to generate first intermediate response data; wherein, the random challenge parameters include at least on-chain challenge parameters generated from on-chain data of the consortium blockchain; The first intermediate response data is input into the SM3 national cryptographic hash function for hash calculation to generate a physical identity response value associated with the acquisition time of the optical acquisition device and random challenge parameters.

7. The product digital identity verification method based on NFT and consortium blockchain according to claim 1, characterized in that, The joint verification based on the data model and the summary data and cross-chain anchoring results in the consortium blockchain is used to determine the consistency of the circulation path, node relationships and time sequence consistency characteristics of the goods in the circulation process, and to obtain the final verification result of the digital identity of the goods, including: Based on the data model, the circulation path, node relationships, and time sequence consistency characteristics of goods in the circulation process are analyzed to establish a commodity circulation consistency verification model. During the digital identity verification process for goods, the consistency of the goods circulation data associated with the NFT digital identity certificate is judged based on the goods circulation consistency verification model, and the corresponding consistency judgment result is output. By combining the summary data in the consortium blockchain and the cross-chain anchoring results formed through the relay chain, the consistency judgment result is verified to obtain the final verification result of the product's digital identity. The consistency determination result and / or the final verification result are hashed to obtain result digest data, and the result digest data is submitted to the parachain of the consortium blockchain for storage and evidence, and cross-chain anchoring is performed through the relay chain.

8. The product digital identity verification method based on NFT and consortium blockchain according to claim 7, characterized in that, Based on the data model, the circulation path, node relationships, and time sequence consistency characteristics of goods in the circulation process are analyzed to establish a commodity circulation consistency verification model, including: Extract commodity circulation data samples from the data model that have been verified to be in normal circulation status and whose corresponding summary data has been stored in the consortium blockchain parallel chain and completed cross-chain anchoring, and use them as training sample sets for normal commodity circulation behavior; Based on the training sample set, the path sequence features, node association features, and temporal change features of goods between different commodity circulation nodes are jointly modeled to generate a feature representation for characterizing the normal circulation behavior pattern of goods. Based on the aforementioned feature representation, a discriminant model is constructed to describe the consistency of cross-border commodity circulation behavior, enabling the discriminant model to quantitatively assess the degree of deviation between the actual circulation status of commodities and the normal circulation behavior pattern. By using historical abnormal flow samples or rule-based abnormal flow samples, the discrimination model is subjected to comparative learning or supervised optimization, so that the discrimination model has the ability to identify abnormal flow paths, abnormal node sequences, and abnormal dwell times.

9. The product digital identity verification method based on NFT and consortium blockchain according to claim 7, characterized in that, In the process of digital identity verification for goods, based on the commodity circulation consistency verification model, the consistency of commodity circulation data associated with the NFT digital identity certificate is judged, and the corresponding consistency judgment result is output, including: Based on the commodity circulation data associated with the NFT digital identity certificate, the actual circulation path of the commodity in the cross-border circulation process is compared and analyzed with the preset standard cross-border circulation path to obtain the path consistency analysis results used to characterize the path consistency. Based on the node timestamp information of each commodity circulation node and the time interval information between adjacent nodes in the commodity circulation data, the temporal change characteristics of commodities between each commodity circulation node are analyzed to obtain the temporal consistency analysis results used to characterize temporal consistency. The path consistency analysis results and the time series consistency analysis results are input into the commodity circulation consistency verification model for joint discrimination, and the consistency judgment result is output to characterize whether the commodity circulation status conforms to the normal circulation behavior pattern.

10. A digital identity verification system for goods based on NFTs and consortium blockchains, characterized in that, The system includes: The input / output module is configured to acquire multi-dimensional status data of goods during the production and circulation process based on IoT acquisition devices. The multi-dimensional status data includes at least one of the following: goods identification information, production information, circulation node information, and time series information. The processing module is configured to generate a unique NFT digital identity credential for the product on a blockchain smart contract based on the multi-dimensional state data, and establish a binding relationship between the NFT digital identity credential and the product's full lifecycle data; wherein the blockchain smart contract is deployed on a consortium blockchain, and the consortium blockchain adopts a chain network architecture including a relay chain and at least one parallel chain; the multi-dimensional state data is encrypted using a national cryptographic algorithm according to the binding relationship, and the encrypted data is hashed to obtain digest data; the digest data is submitted to the parallel chain of the consortium blockchain for notarization, and the notarization result of the parallel chain is cross-chain anchored through the relay chain; the commodity circulation data belonging to the circulation process in the multi-dimensional state data is associated according to the circulation nodes and time sequence to construct a data model for describing the commodity circulation relationship and time sequence characteristics; based on the data model and the digest data in the consortium blockchain and the cross-chain anchoring result, joint verification is performed to determine the consistency of the circulation path, node association relationship and time sequence consistency characteristics of the commodity in the circulation process, and obtain the final verification result of the commodity digital identity.

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