Blockchain-based e-commerce logistics traceability method and system

Abstract

The application discloses an e-commerce logistics tracing method and system based on a blockchain, relates to the technical field of e-commerce logistics tracing, and comprises the following steps: taking a unique commodity identifier as a core key value, and constructing a tracing information index library in combination with node contribution degrees; the application can accurately locate the data storage positions of high-contribution and high-reliability nodes, greatly improves the tracing query efficiency, and avoids resource waste caused by full-chain traversal by quantitatively calculating node contribution degrees, constructing a structured tracing information index library in combination with the unique commodity identifier, the circulation link number and the time stamp; furthermore, a dual quantitative evaluation mechanism of data credibility and query matching degree is established, the authenticity and adaptability of tracing information are scientifically judged, the problem of lack of authoritative evaluation standards in traditional tracing is solved, and the authority of tracing results is strengthened; finally, the dual verification mechanism is checked through block hash verification and node trust value, and the data consistency is quickly checked and the node anomaly is investigated when a user or a supervision party is suspicious.

Description

Technical Field

[0001] This invention relates to the field of e-commerce logistics traceability technology, and in particular to a blockchain-based e-commerce logistics traceability method and system. Background Technology

[0002] With the rapid development of the digital economy, the e-commerce industry has experienced explosive growth. E-commerce logistics, as a key link connecting merchants and consumers, directly impacts the development quality of the e-commerce industry and consumer experience through its end-to-end service quality. E-commerce logistics covers the entire chain of goods from production and processing, warehousing management, trunk transportation, transshipment and distribution to last-mile delivery, involving multiple stakeholders such as e-commerce merchants, logistics companies, manufacturers, and regulatory authorities. E-commerce logistics traceability, as a core link to ensure transparency and standardization of logistics services, aims to achieve the queryability and traceability of information throughout the entire product lifecycle, ensuring that consumers can obtain accurate information about the circulation of goods. At the same time, it provides effective evidence for determining responsibility when quality problems or logistics disputes arise, thereby protecting consumer rights, regulating industry order, and improving logistics efficiency.

[0003] However, current traditional e-commerce logistics traceability relies on centralized platforms to store traceability data, which not only poses security risks such as data tampering and leakage, but also leads to poor data communication among multiple parties, resulting in incomplete and inconsistent traceability information. In addition, traditional traceability methods lack a quantitative information credibility assessment mechanism, making it impossible to scientifically judge the authenticity and reliability of traceability information, resulting in insufficient authority of traceability results and failing to meet the needs of multiple parties for traceability accuracy and security.

[0004] To address the aforementioned technical deficiencies, a solution is proposed. Summary of the Invention

[0005] The purpose of this invention is to address the problems of traditional e-commerce logistics traceability relying on centralized platforms to store traceability data. This not only poses security risks such as data tampering and leakage, but also leads to poor data communication among multiple parties, resulting in incomplete and inconsistent traceability information. Furthermore, traditional traceability methods lack a quantitative information credibility assessment mechanism, making it impossible to scientifically judge the authenticity and reliability of traceability information, resulting in insufficient authority of traceability results and failing to meet the needs of multiple parties for accuracy and security in traceability.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a blockchain-based e-commerce logistics traceability method, comprising the following steps: Step 1: Collect product lifecycle data and generate a unique product identifier through interfaces of e-commerce platform terminals, logistics node IoT devices, production enterprise ERP systems and customs supervision systems. Encrypt the collected product lifecycle data using an asymmetric encryption algorithm to generate ciphertext and digital signature. Step 2: Synchronize the encrypted data and digital signature to each block node of the blockchain consortium chain. Each node performs consistency verification on the encrypted data. After the verification is successful, the consensus node packages the data into a block, generates a new block hash, and writes it into the blockchain. Step 3: Construct a traceability information index database using the product's unique identifier as the core key value and combining it with node contribution. Step 4: Consumers or regulators initiate a traceability query request by entering the product's unique identifier and query keywords through the traceability terminal. Based on the index value in the traceability information index database, the data storage location of high-contribution nodes is located, and the data credibility and query matching degree are calculated simultaneously to filter out traceability information with high credibility and high matching degree. Step 5: If users or regulators have doubts about the traceability results, they can query the corresponding block data in the blockchain explorer using the block hash and automatically perform dual verification.

[0007] Furthermore, the calculation process for node contribution is as follows: S11. Obtain the effective data upload volume and data verification accuracy data of the block node within the period and perform analysis and calculation. S12. Calculate the node contribution using the following formula. : in, This refers to the effective data upload volume within the block node cycle. This represents the maximum effective data upload volume across all block nodes within a given period. This represents the minimum amount of valid data uploaded within the cycle of all block nodes. To verify the accuracy of data within the block node cycle. The average accuracy of data verification across all block nodes within the specified period. The preset data upload weight coefficient, The preset data accuracy weighting coefficient is used to quantify the data contribution and reliability of each blockchain node, and to help build a two-dimensional index so that high-contribution nodes are prioritized for identification.

[0008] Furthermore, the process of building a traceability information index is as follows: S21. Obtain the unique identifier of the product through the system interface. Numbering of each distribution link Data collection timestamps for corresponding stages The unique identifier of the product, the number of the circulation link, and the timestamp are integrated into the characteristic value of the entire product chain; S22. Calculate the index value in the traceability information index database according to the following formula. : in, Number each link in the distribution chain. This represents the total number of links in the distribution chain. As a unique identifier for the product, For the data collection timestamp of the corresponding stage, For the first The contribution of each node, The total number of blockchain nodes. The modulo operation is used to limit the large summation value to the range of blockchain node numbers, ensuring that the index value can accurately match the nodes in the consortium blockchain; S23. Using the generated index value as the association identifier, define the core fields of the index library, associate the characteristic data of each circulation link of the commodity, the corresponding index value, and the core field information of the index library, organize the data according to the hierarchical structure of ID-index value-data location-permission, form a structured traceability information index library, and complete the construction.

[0009] Furthermore, the core fields of the index include: unique product identifier, index value, corresponding node number, node contribution, blockchain block address where the data of each stage of the product is located, encrypted data storage path, and query permission identifier.

[0010] Furthermore, the calculation process for data credibility is as follows: S31. Obtain the historical trust value, data integrity, and data survival time percentage of data nodes and perform analysis and calculation. S32. Calculate the data reliability using the following formula. : in, The historical trust value of the data node. For data integrity, For the percentage of data survival time, The preset trust value weighting coefficient, The preset completeness weighting coefficient, This is the weighting coefficient for time-related degradation. S33. Obtain the preset credibility threshold. With data credibility Comparative analysis, when When data is deemed to have low credibility, it is automatically marked as low credibility and triggers node verification, thereby enhancing the authority of traceability information. Conversely, when data is deemed to have high credibility, it is automatically marked as high credibility and does not require verification.

[0011] Furthermore, the process of calculating the query match rate is as follows: S41. Obtain the correlation between query keywords and process data, as well as the timeliness of the data, and perform analysis and calculation; S42. Calculate the query match degree according to the following formula. : Where E represents the correlation between the query keywords and the process data. For data integrity, C represents data timeliness. The preset correlation weight coefficients, This is a timeliness weighting coefficient; S43. Obtain the preset matching threshold. Matching degree with query Comparative analysis, when If the match is positive, it is classified as a high match; otherwise, it is classified as a low match. This allows us to filter out traceability information that is both highly credible and highly matched.

[0012] Furthermore, the dual verification process is as follows: compare the consistency between the queried block data and the traceability results. If the hash values ​​do not match, an anomaly alarm is triggered. Then, review the calculation process of the data credibility D. If the node trust value T has recent abnormal fluctuations, push the node anomaly information to the regulatory node simultaneously, and start the node qualification review and responsibility traceability process, forming a dual verification of data verification and node supervision.

[0013] The present invention also provides a blockchain-based e-commerce logistics traceability system, including a data acquisition unit, a data uploading unit, an index building unit, an information traceability unit, and a dual verification unit; The data acquisition unit is used to collect product lifecycle data and generate a unique product identifier through interfaces of e-commerce platform terminals, logistics node IoT devices, production enterprise ERP systems and customs supervision systems. The collected product lifecycle data is encrypted using an asymmetric encryption algorithm to generate data ciphertext and digital signature and send them to the data on-chain unit and information traceability unit. The data on-chain unit is used to synchronize the encrypted data and digital signature to each block node of the blockchain consortium chain. Each node performs consistency verification on the encrypted data. After the verification is successful, the consensus node packages the data into blocks, generates a new block hash, and writes it into the blockchain. The index building unit is used to build a traceability information index based on the product's unique identifier as the core key value and combined with the node's contribution. The information traceability unit is used by consumers or regulators to initiate a traceability query request by inputting the unique identifier of the product and query keywords through the traceability terminal. Based on the index value in the traceability information index library, it locates the data storage location of high-contribution nodes and simultaneously calculates the data credibility and query matching degree to filter out traceability information with high credibility and high matching degree. The dual verification unit is used by users or regulators to query the corresponding block data in the blockchain explorer through the block hash if they have doubts about the traceability results, and automatically perform dual verification.

[0014] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: This blockchain-based e-commerce logistics traceability method and system addresses the security risks of data tampering and leakage in traditional centralized storage through a distributed blockchain consortium architecture and asymmetric encryption algorithms. Simultaneously, by collecting data from multiple interfaces of e-commerce platforms, logistics IoT devices, and customs supervision systems, it achieves comprehensive aggregation and synchronous sharing of data across the entire product lifecycle, breaking down data barriers and solving the problems of incomplete and disjointed traceability information. Secondly, by quantifying node contribution and combining unique product identifiers, circulation link numbers, and timestamps to construct a structured traceability information index, it can accurately locate the data storage locations of high-contribution, high-reliability nodes, significantly improving traceability query efficiency and avoiding the waste of resources from full-chain traversal. Thirdly, it establishes a dual quantitative evaluation mechanism for data credibility and query matching, scientifically judging the authenticity and suitability of traceability information, solving the problem of the lack of authoritative evaluation standards in traditional traceability, and strengthening the authority of traceability results. Finally, the dual verification mechanism, through block hash verification and node trust value review, quickly checks data consistency and identifies node anomalies when users or regulators have doubts. Attached Figure Description

[0015] Figure 1 A schematic diagram of the method flow of the present invention is shown; Figure 2 A schematic diagram of the system flow of the present invention is shown. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Example 1: like Figure 1As shown, the blockchain-based e-commerce logistics traceability method first collects product lifecycle data and generates a unique product identifier through interfaces with e-commerce platform terminals, IoT devices at logistics nodes (GPS positioning modules, temperature and humidity sensors), and the customs supervision system. This data includes basic product information (name, specifications, production batch), production data (production date, quality inspection results), logistics data (transport vehicle information, real-time location, node arrival time), warehousing data (warehousing time, inventory status), and delivery data (recipient, receipt time). The collected product lifecycle data is then encrypted using an asymmetric encryption algorithm (RSA algorithm) to generate encrypted data and a digital signature, ensuring the security of data transmission. Then, the encrypted data and digital signature are synchronized to all block nodes (e-commerce nodes, logistics nodes, production nodes, and regulatory nodes) of the blockchain consortium chain. Each node verifies the consistency of the encrypted data. After successful verification, the consensus node (using the PBFT consensus mechanism) packages the data into blocks. Each block contains the hash value of the previous block, the data digest of the current block, and a timestamp. A new block hash is generated and written to the blockchain, achieving immutable data storage. Each node synchronously updates the blockchain ledger to ensure data consistency across all parties. Then, using the unique identifier of the product (such as the product traceability code) as the core key value, and combining it with the node contribution, a traceability information index is built; The calculation process for node contribution is as follows: S11. Obtain the effective data upload volume and data verification accuracy rate of the block node within the period and perform analysis and calculation. It should be noted that the effective data upload volume within the period refers to the upload volume after removing duplicate and invalid data, and the data verification accuracy rate within the period refers to the ratio of the number of times the node's verification result is consistent with the consensus result of the consortium chain when participating in the data verification of other nodes within the statistical period to the total number of times the node participates in the data verification of other nodes within the statistical period. S12. Calculate the node contribution using the following formula. : in, This refers to the effective data upload volume within the block node cycle. This represents the maximum effective data upload volume across all block nodes within a given period. This represents the minimum amount of valid data uploaded within the cycle of all block nodes. To verify the accuracy of data within the block node cycle. The average accuracy of data verification across all block nodes within the specified period. The preset data upload weight coefficient, The preset data accuracy weighting coefficient and node contribution are used to quantify the data contribution and reliability of each blockchain node, and to help build a two-dimensional index so that high-contribution nodes (those with more data uploads and accurate verification) are prioritized for location, thereby improving the efficiency of traceability and query, while ensuring that the data retrieved is more reliable.

[0018] The process of building a traceability information index is as follows: S21. Obtain the unique identifier of the product through the system interface. Numbering of each distribution link ( =1,2,...,n, where 1 represents production, 2 represents warehousing, ...,n represents delivery), corresponding to the data collection timestamps of each stage. This integrates the product's unique identifier, distribution link number, and timestamp into a full-chain feature value for the product, strengthening the unique association between the product and specific distribution links; S22. Calculate the index value in the traceability information index database according to the following formula. : in, Number each link in the distribution chain. This represents the total number of links in the distribution chain. As a unique identifier for the product, For the data collection timestamp of the corresponding stage, For the first The contribution of each node, The total number of blockchain nodes. The modulo operation is used to limit the summation of large values ​​to a range of blockchain node numbers, ensuring that the index value accurately matches the nodes in the consortium blockchain. It should be noted that the divisor N in the formula is the total number of blockchain nodes. The final index value is obtained through the modulo operation. It must fall within the interval [0, N-1], which corresponds exactly to the node number of the consortium blockchain (e.g., when N=5). It can only be 0, 1, 2, 3, or 4). S23. Using the generated index value as the association identifier, define the core fields of the index library, and associate the characteristic data of each link in the product circulation process, the corresponding index values, and the core field information of the index library. Organize the data according to the hierarchical structure of ID-index value-data location-permission to form a structured traceability information index library, thus completing the construction. By associating the entire product chain data through a two-dimensional index of "product characteristics-node contribution," not only is the blockchain traversal range reduced, but the data stored by high-contribution nodes is also prioritized, further improving query efficiency. It should be noted that the core fields of the index library include: unique product identifier, index value, corresponding node number, node contribution, blockchain block address where the data of each link in the product is located, encrypted data storage path, and query permission identifier (distinguishing the query scope for consumers / regulators / merchants).

[0019] Subsequently, consumers or regulators can initiate a traceability query request by entering the product's unique identifier and query keywords (such as "transportation temperature" or "quality inspection report") through traceability terminals (such as e-commerce apps or WeChat mini programs). Based on the index values ​​in the traceability information index database, the data storage location of high-contribution nodes is located, and the data credibility and query matching degree are calculated simultaneously to filter out traceability information with high credibility and high matching degree. The calculation process for data credibility is as follows: S31. Obtain the historical trust value, data integrity, and data survival time percentage of data nodes and perform analysis and calculation. S32. Calculate the data reliability using the following formula. : in, The historical trust value of the data node (T∈[0,1], calculated in reverse from the abnormal data rate of the node). For data integrity (H∈[0,1]). The percentage of data survival time (K = current duration / commodity logistics cycle, K∈[0,1], used to reflect data timeliness). The preset trust value weighting coefficient, The preset completeness weighting coefficient, As for the time-related decay weighting coefficient, it should be noted that... 'a' can take the value 0.6, and 'b' can take the value 0.3. The value can be 0.2, with the preset trust value weight coefficient being the highest, used to ensure that data from high-trust nodes is prioritized for acceptance; the preset integrity weight coefficient is used to supplement the data quality assessment itself; the K item introduces a timeliness decay weight coefficient, which is used to explain that the longer the data survives within the logistics cycle (such as historical warehouse data near delivery), the lower the credibility (1-0.2K), which meets the actual need for more traceable data in the near term. S33. Obtain the preset credibility threshold. With data credibility Comparative analysis, when When data is deemed to have low credibility, it is automatically marked as low credibility and triggers node verification, thereby enhancing the authority of traceability information. Conversely, when data is deemed to have high credibility, it is automatically marked as high credibility and does not require verification.

[0020] The process of calculating the query match score is as follows: S41. Obtain the correlation between query keywords and process data, as well as the timeliness of the data, and perform analysis and calculation; S42. Calculate the query match degree according to the following formula. : Where E is the correlation between the query keywords and the process data (E∈[0,1], calculated by the cosine similarity algorithm). For data integrity ( ∈[0,1]), C represents the timeliness of the data (C∈[0,1], the smaller the difference between the current time and the data collection time, the closer C is to 1). The preset correlation weight coefficients, Timeliness weighting coefficient ( The values ​​are obtained through training based on user query history and are considered normal values. ); S43. Obtain the preset matching threshold. Matching degree with query Comparative analysis, when If the match is positive, it is classified as a high match; otherwise, it is classified as a low match. This allows us to filter out traceability information that is both highly credible and highly matched.

[0021] Finally, if users or regulators have doubts about the traceability results, they can query the corresponding block data in the blockchain explorer using the block hash and automatically perform dual verification. The dual verification process is as follows: compare the consistency between the queried block data and the traceability results. If the hash values ​​do not match, an anomaly alarm is triggered. Then, the calculation process of the data credibility D is reviewed. If the node trust value T has recently experienced abnormal fluctuations (such as T dropping sharply from 0.9 to 0.3), the node anomaly information is pushed to the regulatory node simultaneously, initiating the node qualification review and responsibility traceability process, thus forming dual verification of data verification and node supervision.

[0022] Example 2: like Figure 2 As shown, the blockchain-based e-commerce logistics traceability system is applied to the blockchain-based e-commerce logistics traceability method, including a data collection unit, a data uploading unit, an index construction unit, an information traceability unit, and a dual verification unit. The data acquisition unit is used to collect product lifecycle data and generate a unique product identifier through interfaces of e-commerce platform terminals, logistics node IoT devices, production enterprise ERP systems and customs supervision systems. The collected product lifecycle data is encrypted using an asymmetric encryption algorithm to generate data ciphertext and digital signature and send them to the data on-chain unit and information traceability unit. The data on-chain unit is used to synchronize the encrypted data and digital signature to each block node of the blockchain consortium chain. Each node performs consistency verification on the encrypted data. After the verification is successful, the consensus node packages the data into blocks, generates a new block hash, and writes it into the blockchain. The index building unit is used to build a traceability information index based on the product's unique identifier as the core key value and combined with the node's contribution. The information traceability unit is used by consumers or regulators to initiate a traceability query request by inputting the unique identifier of the product and query keywords through the traceability terminal. Based on the index value in the traceability information index library, it locates the data storage location of high-contribution nodes and simultaneously calculates the data credibility and query matching degree to filter out traceability information with high credibility and high matching degree. The dual-verification unit is used by users or regulators who have doubts about the traceability results. They can query the corresponding block data in the blockchain explorer using the block hash and automatically perform dual verification. This invention addresses the security risks of data tampering and leakage in traditional centralized storage through a distributed blockchain consortium architecture and asymmetric encryption algorithms. Simultaneously, by collecting data from multiple interfaces of e-commerce platforms, logistics IoT devices, and customs supervision systems, it achieves comprehensive aggregation and synchronous sharing of data across the entire product lifecycle, breaking down data barriers and solving the problems of incomplete and disjointed traceability information. Secondly, by quantifying node contribution and combining it with unique product identifiers, circulation link numbers, and timestamps to construct a structured traceability information index, it can accurately locate the data storage locations of high-contribution, high-reliability nodes, significantly improving traceability query efficiency and avoiding the waste of resources from full-chain traversal. Thirdly, it establishes a dual quantitative evaluation mechanism for data credibility and query matching, scientifically judging the authenticity and suitability of traceability information, solving the problem of traditional traceability lacking authoritative evaluation standards, and strengthening the authority of traceability results. Finally, the dual verification mechanism, through block hash verification and node trust value review, quickly checks data consistency and identifies node anomalies when users or regulators have doubts.

[0023] The size of the interval and threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by those skilled in the art for each set of sample data; as long as it does not affect the ratio between the parameter and the quantized value.

[0024] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation. The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A blockchain-based e-commerce logistics traceability method, characterized in that, Includes the following steps: Step 1: Collect product lifecycle data and generate a unique product identifier through the interfaces of e-commerce platform terminals, logistics node IoT devices and customs supervision system. Encrypt the collected product lifecycle data using an asymmetric encryption algorithm to generate ciphertext and digital signature. Step 2: Synchronize the encrypted data and digital signature to each block node of the blockchain consortium chain. Each node performs consistency verification on the encrypted data. After the verification is successful, the consensus node packages the data into a block, generates a new block hash, and writes it into the blockchain. Step 3: Construct a traceability information index database using the product's unique identifier as the core key value and combining it with node contribution. Step 4: Consumers or regulators initiate a traceability query request by entering the product's unique identifier and query keywords through the traceability terminal. Based on the index value in the traceability information index database, the data storage location of high-contribution nodes is located, and the data credibility and query matching degree are calculated simultaneously to filter out traceability information with high credibility and high matching degree. Step 5: If users or regulators have doubts about the traceability results, they can query the corresponding block data in the blockchain explorer using the block hash and automatically perform dual verification.

2. The blockchain-based e-commerce logistics traceability method according to claim 1, characterized in that, The calculation process for node contribution is as follows: S11. Obtain the effective data upload volume and data verification accuracy data of the block node within the period and perform analysis and calculation. S12. Calculate the node contribution using the following formula. : in, This refers to the effective data upload volume within the block node cycle. This represents the maximum effective data upload volume across all block nodes within a given period. This represents the minimum amount of valid data uploaded within the cycle of all block nodes. To verify the accuracy of data within the block node cycle. The average accuracy of data verification across all block nodes within the specified period. The preset data upload weight coefficient, The preset data accuracy weighting coefficient is used to quantify the data contribution and reliability of each blockchain node, and to help build a two-dimensional index so that high-contribution nodes are prioritized for identification.

3. The blockchain-based e-commerce logistics traceability method according to claim 1, characterized in that, The process of building a traceability information index is as follows: S21. Obtain the unique identifier of the product through the system interface. Numbering of each distribution link Data collection timestamps for corresponding stages The unique identifier of the product, the number of the circulation link, and the timestamp are integrated into the characteristic value of the entire product chain; S22. Calculate the index value in the traceability information index database according to the following formula. : in, Number each link in the distribution chain. This represents the total number of links in the distribution chain. As a unique identifier for the product, For the data collection timestamp of the corresponding stage, For the first The contribution of each node, The total number of blockchain nodes. The modulo operation is used to limit the large summation value to the range of blockchain node numbers, ensuring that the index value can accurately match the nodes in the consortium blockchain; S23. Using the generated index value as the association identifier, define the core fields of the index library, associate the characteristic data of each circulation link of the commodity, the corresponding index value, and the core field information of the index library, organize the data according to the hierarchical structure of ID-index value-data location-permission, form a structured traceability information index library, and complete the construction.

4. The blockchain-based e-commerce logistics traceability method according to claim 3, characterized in that, The core fields of the index include: unique product identifier, index value, corresponding node number, node contribution, blockchain block address where the data of each stage of the product is located, encrypted data storage path, and query permission identifier.

5. The blockchain-based e-commerce logistics traceability method according to claim 1, characterized in that, The calculation process for data credibility is as follows: S31. Obtain the historical trust value, data integrity, and data survival time percentage of data nodes and perform analysis and calculation. S32. Calculate the data reliability using the following formula. : in, The historical trust value of the data node. For data integrity, For the percentage of data survival time, The preset trust value weighting coefficient, The preset completeness weighting coefficient, This is the weighting coefficient for time-related degradation. S33. Obtain the preset credibility threshold. With data credibility Comparative analysis, when When data is deemed to have low credibility, it is automatically marked as low credibility and triggers node verification, thereby enhancing the authority of traceability information. Conversely, when data is deemed to have high credibility, it is automatically marked as high credibility and does not require verification.

6. The blockchain-based e-commerce logistics traceability method according to claim 1, characterized in that, The process of calculating the query match score is as follows: S41. Obtain the correlation between query keywords and process data, as well as the timeliness of the data, and perform analysis and calculation; S42. Calculate the query match degree according to the following formula. : Where E represents the correlation between the query keywords and the process data. For data integrity, C represents data timeliness. The preset correlation weight coefficients, This is a timeliness weighting coefficient; S43. Obtain the preset matching threshold. Matching degree with query Comparative analysis, when If the match is positive, it is classified as a high match; otherwise, it is classified as a low match. This allows us to filter out traceability information that is both highly credible and highly matched.

7. The blockchain-based e-commerce logistics traceability method according to claim 1, characterized in that, The dual verification process is as follows: compare the consistency between the queried block data and the traceability results. If the hash values ​​do not match, an anomaly alarm is triggered. Then, the calculation process of the data credibility D is reviewed. If the node trust value T has recent abnormal fluctuations, the node anomaly information is pushed to the regulatory node simultaneously, and the node qualification review and responsibility traceability process is initiated, forming a dual verification of data verification and node supervision.

8. A blockchain-based e-commerce logistics traceability system, applied to the blockchain-based e-commerce logistics traceability method described in any one of claims 1-7, characterized in that, It includes a data acquisition unit, a data upload unit, an index building unit, an information traceability unit, and a dual verification unit; The data acquisition unit is used to collect product lifecycle data and generate a unique product identifier through interfaces of e-commerce platform terminals, logistics node IoT devices, production enterprise ERP systems and customs supervision systems. The collected product lifecycle data is encrypted using an asymmetric encryption algorithm to generate data ciphertext and digital signature and send them to the data on-chain unit and information traceability unit. The data on-chain unit is used to synchronize the encrypted data and digital signature to each block node of the blockchain consortium chain. Each node performs consistency verification on the encrypted data. After the verification is successful, the consensus node packages the data into blocks, generates a new block hash, and writes it into the blockchain. The index building unit is used to build a traceability information index based on the product's unique identifier as the core key value and combined with the node's contribution. The information traceability unit is used by consumers or regulators to initiate a traceability query request by inputting the unique identifier of the product and query keywords through the traceability terminal. Based on the index value in the traceability information index library, it locates the data storage location of high-contribution nodes and simultaneously calculates the data credibility and query matching degree to filter out traceability information with high credibility and high matching degree. The dual verification unit is used by users or regulators to query the corresponding block data in the blockchain explorer through the block hash if they have doubts about the traceability results, and automatically perform dual verification.

Images