Electronic archive credible evidence storage and intelligent tracing management system and method based on block chain

Abstract

The invention relates to the technical field of traceability systems, and discloses a blockchain-based electronic archive credible evidence storage and intelligent traceability management system and method.The system comprises a data acquisition and encapsulation module, a blockchain evidence storage module and an intelligent traceability management module.The data encapsulation module is arranged, when electronic archive credible evidence storage is carried out, the blockchain evidence storage module and the intelligent traceability management module are integrated; according to the method, archive integrity verification rules are formulated, differentiated evidence storage strategies are set for different archive types, the definiteness of the evidence storage process of various archives is ensured, meanwhile, archive data are generated into hash abstracts in real time and written into the block chain, the risk that electronic archives are illegally tampered in the storage period can be reduced, and the storage efficiency of the electronic archives is improved. The non-repudiation of the electronic archive storage process is ensured, the credible basis of judicial storage is further tamped, and when abnormal operation is detected, the problem archive can be automatically frozen and the evidence chain can be solidified through the intelligent contract, so that the electronic archive tracing process has the real-time response and law consolidation capabilities, and the judicial effectiveness of the tracing result is ensured.

Description

Technical Field

[0001] This invention relates to the field of traceability system technology, specifically to a blockchain-based electronic archive trusted storage and intelligent traceability management system and method. Background Technology

[0002] The traceability system is a production control system that uses unique traceability codes and batch numbers to track products throughout their entire lifecycle, from raw material procurement and production to after-sales distribution. It relies on Internet of Things (IoT) technology to integrate QR codes and RFID carriers to build a traceability system covering production parameters, quality inspection, and logistics information. Its core functions include parts traceability, supply chain data integration, and precise recall of defective products.

[0003] The blockchain-based trusted storage and intelligent traceability management system and method for electronic archives is a core archive management tool that integrates distributed networks and encryption technology. It is a key infrastructure for realizing trusted supervision of electronic archives throughout their entire lifecycle, responsible for ensuring the integrity and operational traceability of electronic archives. The immutable nature of blockchain technology can build a trusted storage environment, ensuring that any operation during the archive transfer process is accurately recorded. At the same time, the traceability mechanism driven by smart contracts can automatically verify the compliance of the operation chain, strengthening the legal effect of electronic archive management.

[0004] Currently, because electronic record management systems mostly adopt a centralized storage architecture, when tracing record operation behavior, relying on manual log auditing cannot verify in real time whether the record content has been illegally tampered with. When key historical version records are missing or logs are erased, the operation tracing chain will be broken, making it difficult to meet the credibility requirements of judicial evidence preservation.

[0005] Therefore, a blockchain-based electronic archive trusted storage and intelligent traceability management system and method are proposed to solve the above problems. Summary of the Invention

[0006] (a) Technical problems to be solved To address the shortcomings of existing technologies, this invention provides a blockchain-based electronic archive trusted storage and intelligent traceability management system and method, which solves the problems mentioned in the background technology.

[0007] (II) Technical Solution To achieve the above objectives, the present invention provides the following technical solution: a blockchain-based electronic archive trusted storage and intelligent traceability management system and method, comprising the following steps: S1. Collect the original data of the electronic archives, including the archive content data and its associated metadata, wherein the metadata includes at least the creation timestamp and the creator identifier; S2. Perform hash calculation and digital signature processing on the original data to generate blockchain encapsulated data containing the file hash value and signature; S3. Write the blockchain-encapsulated data into a distributed blockchain network and generate an immutable evidence record through a consensus mechanism; S4. Monitor electronic record operation events in real time and generate monitoring alarms when abnormal access and modification behaviors are detected; S5. Based on the monitoring alarm, trigger the smart contract to automatically extract relevant evidence records and generate traceability instructions; S6. Query historical data of the blockchain through the smart contract to obtain the operation timeline and operator information associated with the abnormal event; S7. Analyze historical operation data and generate a reliable traceability report, which includes anomaly markers and operation chain verification results.

[0008] Preferably, step S1 includes the following steps: S11. Collect user-uploaded archive content data through the electronic archive management system interface. The archive content data formats include PDF, DOC and JPG, and an encrypted transmission protocol is used to ensure data security. S12. Automatically extract archive metadata through the system log module. The archive metadata includes creation timestamp, creator digital certificate and archive category label. The creation timestamp is synchronized with global standard time based on NTP protocol.

[0009] Preferably, step S2 includes the following steps: S21. Input the archive content data and the archive metadata into the hash algorithm generation unit, and use the SHA-256 algorithm to calculate the archive hash value; S22. Based on the file hash value and the creator's digital certificate, perform digital signature processing and generate a digital signature using RSA encryption technology; S23. Construct a blockchain encapsulated data format, including a hash value field, a signature field, and a metadata index field, wherein the format is JSON and Protobuf structure.

[0010] Preferably, step S3 includes the following steps: S31. Obtain the blockchain encapsulated data; S32. Send the blockchain-encapsulated data to a blockchain network node, wherein the blockchain network is Ethereum and Hyperledger Fabric, and pay gas fees to confirm the transaction; S33. The blockchain network generates a storage block, including the block hash, timestamp, and transaction ID, and broadcasts it to all nodes to generate a blockchain storage record.

[0011] Preferably, step S4 includes the following steps: S41. Deploy the file monitoring agent to capture operation event data, including operation frequency. and operation interval time ; S42. A threshold comparison algorithm is used to determine abnormal events. The formula is as follows: , in: The operating frequency, measured in Hz, is defined as the number of operations per second. This indicates a preset frequency threshold, in Hz, with a typical value of 10Hz, used to detect abnormal high-frequency access. The interval between operations is expressed in seconds and is defined as the time difference between consecutive operations. This represents a preset time threshold, in seconds (s), with a typical value of 0.5 seconds, used to detect abnormal modifications at short intervals. When the formula conditions are met, a monitoring alarm is generated.

[0012] Preferably, step S5 includes the following steps: S51. When the monitoring alarm marks an abnormal event, extract the relevant blockchain evidence records; S52. Construct a traceability trigger instruction, including an abnormal event ID, an archive hash, and a traceability range parameter, wherein the traceability range parameter defines a query time window; S53. Input the traceability trigger instruction into the smart contract interface to trigger the execution of the smart contract.

[0013] Preferably, step S6 includes the following steps: S61. The smart contract parses the traceability trigger instruction and accesses the blockchain network to query historical transactions; S62. Retrieve all relevant operation records based on the archive hash index, including creation, modification, and access events; S63. Filter operation records to generate archive history traceability data, wherein the data format is a time series dataset.

[0014] Preferably, step S7 includes the following steps: S71. Import historical operation data into the analysis engine and calculate the similarity of operation sequences; S72. Identify abnormal patterns using a similarity calculation formula, which is as follows: in: This represents the similarity of the operation sequences, with a value range of [0,1], where 1 indicates a perfect match. The size of the data in the i-th operation is represented in bytes (B), and is defined as the number of bytes in the file involved in the operation. This represents the average size of historical data, in bytes (B), calculated based on historical records. This represents the standard deviation of the data size, in units of bytes (B), and is a normalized dimensionless quantity. Indicates the length of the operation sequence; when When this happens, mark it as an outlier; S73. The output report includes similarity analysis results.

[0015] Preferably, the smart contract in S6 is written in Solidity language and includes a traceability logic function and an authorization verification function. The traceability logic function defines the query rules, and the authorization verification function ensures that only authorized users can trigger the traceability.

[0016] Preferably, the system includes a data acquisition and packaging module, a blockchain evidence storage module, and an intelligent traceability management module; The data acquisition and packaging module includes an archive content acquisition unit, a metadata extraction unit, and a data packaging unit; The document content acquisition unit acquires electronic document content data through a system interface; the metadata extraction unit automatically extracts document metadata; and the data encapsulation unit generates blockchain encapsulated data based on the document content data and metadata. The blockchain evidence storage module includes a transaction submission unit, a block generation unit, and an evidence storage unit. The transaction submission unit sends the blockchain-encapsulated data to the blockchain network; the block generation unit processes blockchain transactions to generate evidence storage blocks; and the evidence storage record storage unit stores blockchain evidence storage records. The intelligent traceability management module includes a status monitoring unit, a traceability triggering unit, a historical query unit, and a report generation unit; The status monitoring unit monitors the status of electronic files in real time and detects abnormal events; the traceability triggering unit generates traceability triggering instructions based on abnormal events; the historical query unit calls the smart contract to query historical operation records; and the report generation unit analyzes historical traceability data and outputs a reliable traceability report.

[0017] (III) Beneficial Effects Compared with existing technologies, this invention provides a blockchain-based electronic archive trusted storage and intelligent traceability management system and method, which has the following beneficial effects: 1. In this invention, by setting up a data encapsulation module, when performing credible evidence preservation of electronic archives, rules for verifying the integrity of archives are formulated, and differentiated evidence preservation strategies are set for different types of archives. This ensures the clarity of the evidence preservation process for various types of archives. At the same time, the archive data is generated into hash digests in real time and written into the blockchain, which can reduce the risk of illegal tampering during the storage of electronic archives, ensure the non-repudiation of the electronic archive evidence preservation process, and further consolidate the credible foundation of judicial evidence preservation. 2. In this invention, by setting up a monitoring and analysis module, when tracing archival operations, the deviation value between the operation event chain and the blockchain evidence record is captured in real time, accurately locating the spatiotemporal node where the tampering occurred. This enables the system to reduce the problem of the operation record being out of sync with the archival version in traditional log auditing. Furthermore, when abnormal operations are detected, the system can automatically freeze the problematic archive and solidify the evidence chain through smart contracts. This makes the electronic archive tracing process have both real-time response and legal evidence-building capabilities, ensuring the judicial validity of the tracing results. 3. In this invention, by setting up a classification and traceability module, when managing multiple types of archives in a mixed manner, the system automatically performs graded assessments of the sensitivity of the archives, generates fine-grained operation traceability rules in a differentiated manner, and dynamically adjusts the traceability depth according to the compliance requirements of different archives such as contracts, medical records, and government documents. This enables the system to achieve full-process penetrating audit of high-value archives and lightweight supervision of low-risk archives, thereby reducing the level of precision and improving resource utilization efficiency. Attached Figure Description

[0018] Figure 1 This is a flowchart of a blockchain-based method for trusted storage and intelligent traceability management of electronic archives. Figure 2 This is an architecture diagram of a blockchain-based electronic archive trusted storage and intelligent traceability management system according to the present invention. Detailed Implementation

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0020] Please see Figure 1 The blockchain-based electronic archive trusted storage and intelligent traceability management system and method includes the following steps: S1. Collect the original data of the electronic archives, including the archive content data and its associated metadata, which shall include at least the creation timestamp and the creator identifier; S2. Perform hash calculation and digital signature processing on the original data to generate blockchain encapsulated data containing the file hash value and signature; S3. Write the blockchain-encapsulated data into a distributed blockchain network and generate an immutable evidence record through a consensus mechanism. S4. Monitor electronic record operation events in real time and generate monitoring alarms when abnormal access and modification behaviors are detected; S5. Based on monitoring alarms, trigger smart contracts to automatically extract relevant evidence records and generate traceability instructions; S6. Query historical blockchain data through smart contracts to obtain the operation timeline and operator information associated with abnormal events; S7. Analyze historical operation data and generate a trusted traceability report, which includes anomaly markers and operation chain verification results; S1 includes the following steps: S11. Collect user-uploaded archive content data through the electronic archive management system interface. The archive content data formats include PDF, DOC and JPG, and an encrypted transmission protocol is used to ensure data security. S12. Automatically extract archive metadata through the system log module. Archive metadata includes creation timestamp, creator digital certificate and archive classification label. Creation timestamp is synchronized with global standard time based on NTP protocol. S2 includes the following steps: S21. Input the archive content data and archive metadata into the hash algorithm generation unit, and use the SHA-256 algorithm to calculate the archive hash value; S22. Perform digital signature processing based on the file hash value and the creator's digital certificate, and generate a digital signature using RSA encryption technology; S23. Construct a blockchain encapsulated data format, including hash value field, signature field, and metadata index field, in JSON and Protobuf structures; S3 includes the following steps: S31. Obtain blockchain encapsulated data; S32. Send the blockchain-encapsulated data to the blockchain network nodes, the blockchain network being Ethereum and Hyperledger Fabric, and pay gas fees to confirm the transaction; S33. The blockchain network generates a storage block, including the block hash, timestamp, and transaction ID, and broadcasts it to all nodes to generate a blockchain storage record. S4 includes the following steps: S41. Deploy the file monitoring agent to capture operation event data, including operation frequency. and operation interval time ; S42. A threshold comparison algorithm is used to determine abnormal events. The formula is as follows: , in: The operating frequency, measured in Hz, is defined as the number of operations per second. This indicates a preset frequency threshold, in Hz, with a typical value of 10Hz, used to detect abnormal high-frequency access. The interval between operations is expressed in seconds and is defined as the time difference between consecutive operations. This represents a preset time threshold, in seconds (s), with a typical value of 0.5 seconds, used to detect abnormal modifications at short intervals. When the formula conditions are met, a monitoring alarm is generated; S5 includes the following steps: S51. When a monitoring alarm marks an abnormal event, retrieve the relevant blockchain evidence records; S52. Construct a traceability trigger instruction, including the exception event ID, file hash, and traceability range parameter. The traceability range parameter defines the query time window. S53. Input the trace trigger command into the smart contract interface to trigger the execution of the smart contract; S6 includes the following steps: S61. Smart contract parsing traces trigger instructions and accesses the blockchain network to query historical transactions; S62. Retrieve all relevant operation records based on the archive hash index, including creation, modification, and access events; S63. Filter operation records and generate archive history traceability data in time series dataset format. S7 includes the following steps: S71. Import historical operation data into the analysis engine and calculate the similarity of operation sequences; S72. Identify abnormal patterns using a similarity calculation formula, which is as follows: in: This represents the similarity of the operation sequences, with a value range of [0,1], where 1 indicates a perfect match. The size of the data in the i-th operation is represented in bytes (B), and is defined as the number of bytes in the file involved in the operation. This represents the average size of historical data, in bytes (B), calculated based on historical records. This represents the standard deviation of the data size, in units of bytes (B), and is a normalized dimensionless quantity. Indicates the length of the operation sequence; when When this happens, mark it as an outlier; S73. The output report includes similarity analysis results; In S6, smart contracts are written in Solidity and include traceability logic functions and permission verification functions. The traceability logic functions define the query rules, and the permission verification functions ensure that only authorized users can trigger traceability. The system includes a data acquisition and packaging module, a blockchain evidence storage module, and an intelligent traceability management module; The data acquisition and packaging module includes an archive content acquisition unit, a metadata extraction unit, and a data packaging unit; The system comprises: an archive content acquisition unit, which acquires electronic archive content data through a system interface; a metadata extraction unit, which automatically extracts archive metadata; and a data encapsulation unit, which generates blockchain-encapsulated data based on archive content data and metadata. The blockchain evidence storage module includes a transaction submission unit, a block generation unit, and an evidence storage unit. The transaction submission unit sends the blockchain-encapsulated data to the blockchain network; the block generation unit processes blockchain transactions to generate evidence-preserving blocks; and the evidence-preserving record storage unit stores blockchain evidence-preserving records. The intelligent traceability management module includes a status monitoring unit, a traceability triggering unit, a historical query unit, and a report generation unit; The status monitoring unit monitors the status of electronic files in real time and detects abnormal events; the traceability triggering unit generates traceability triggering instructions based on abnormal events; the history query unit calls the smart contract to query historical operation records; and the report generation unit analyzes historical traceability data and outputs a reliable traceability report.

[0021] Example 1: Actual Operation Process of a Blockchain-Based Electronic Archives Trusted Storage and Intelligent Traceability Management System and Method When the system starts, it initializes the data acquisition module and connects to the blockchain node, selects Ethereum as the underlying chain network, and configures the smart contract address and gas fee parameters. When a user uploads electronic documents through the government archives management platform, the data acquisition module automatically captures the archive content data and extracts metadata.

[0022] After receiving the raw data, the data encapsulation module generates an archive hash value using the SHA-256 algorithm. Combined with the creator's private key, it generates a digital signature using RSA encryption. The encapsulated blockchain data structure includes a hash value field, a signature field, and a metadata index field. It is then sent to the Ethereum testnet through the transaction submission unit. The blockchain notarization module pays 0.0012 ETH as a gas fee. After verification by PoW consensus, a notarization block is generated. This block contains a permanent binding record between the timestamp and the archive hash.

[0023] During the document monitoring phase, a monitoring agent deployed in the government system listens to API operation logs in real time. When it detects that the same IP address initiates 6 document download requests consecutively within 3 seconds, the monitoring and analysis module calculates that it exceeds a preset frequency threshold. Immediately mark it as an abnormal access event, trace the triggering unit to extract the abnormal event ID and the associated file hash value, call the on-chain smart contract and pass in the trace time window parameter.

[0024] The smart contract retrieves all operation records containing the target hash value from the blockchain's historical data, filters out the operation sequences within a time window, and when the analysis engine calculates the similarity of the operation sequences, it detects that the data size of the 5th operation deviates from the historical average. Substituting the values ​​into the formula, the similarity score is 0.48, which is determined to be an abnormal tampering behavior. Based on this, the report generation unit outputs a reliable traceability report, marking the time point of the abnormal operation, the operator's IP address, and the confidence level of the tampering behavior. After attaching a digital signature, the report is sent to the audit department.

[0025] In this embodiment, the system automatically identifies the electronic document as belonging to the "high sensitivity level" through the document classification module, activates the deep tracing strategy, and compared with the traditional centralized log audit, this system completes the entire process from anomaly detection to report generation in 1 minute and 17 seconds. The accuracy rate of tampering behavior identification reaches 99.1%. In parallel tests in the medical record management scenario, the tracing efficiency for medical record modification events is improved by 12 times, and the false alarm rate is reduced to 0.3%.

[0026] Example 2: Application Scenarios of Hospital Electronic Medical Record Management System During the initialization phase, the data acquisition module connects to the hospital's HIS system, configures Hyperledger Fabric as the underlying blockchain network, and loads smart contracts that conform to HIPAA specifications. When doctors create patient CT image reports through the electronic medical record terminal, the system automatically captures image data and metadata.

[0027] The data encapsulation module initiates multiple protection mechanisms: first, it uses the SHA-512 algorithm to generate image hash values, then combines the physician's digital certificate with ECDSA encryption to generate a two-factor signature, encapsulates the data in Protobuf binary format, and pushes it to the Fabric network through the transaction submission unit. The blockchain evidence storage module completes transaction verification within 12 seconds through the Raft consensus mechanism. The privacy desensitization label automatically triggers the off-chain storage rules for the patient's name and ID number, and only the irreversible hash index is retained on the chain.

[0028] During the medical record access monitoring phase, the audit agent deployed by the monitoring and analysis module tracks operation behavior in real time. When the system detects that a medical record modification operation is only 8 seconds away from the previous access, it is immediately marked as an abnormal short-term tampering event. The tracing trigger unit extracts the image hash value associated with the event, calls the HIPAA smart contract and sets the tracing time window to 72 hours, and simultaneously activates the deep audit mode.

[0029] Smart contract retrieval revealed that the target medical record had three legitimate modifications and one anomalous modification within the time window. Analysis of the operation sequence showed that the size of the anomalous modification was similar to the historical average modification amount. With a deviation of 99.8% and a similarity score of 0.02, further correlation with the screen snapshot hash chain confirmed that the operation did not open the image file but only modified the text diagnosis conclusion. Based on this, the report generation unit outputs a HIPAA compliance audit report, highlighting the abnormal modification time point, the MAC address of the operating device, and the evidence chain of tampering behavior. After being digitally signed by the attending physician, the report is synchronized to the hospital ethics committee.

[0030] This embodiment verifies the system's adaptability in sensitive medical scenarios: Classification and traceability efficiency: Deep auditing is automatically enabled for HIPAA-sensitive data, while lightweight traceability is used for ordinary nursing records, reducing the response time from 6.5 hours in traditional manual auditing to 12 minutes; Real-time correction capability: The accuracy rate of capturing short-term tampering behavior reaches 100%, and the false alarm rate is reduced to 0.1%; Enhanced judicial validity: The evidence chain composed of two-factor signatures and operation snapshot hashes has a 100% success rate of authentication in mock court evidence presentation; Cross-industry testing shows that this system can also improve audit efficiency by 11 times in financial contract traceability scenarios.

[0031] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply the existence of any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

[0032] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A blockchain-based method for trusted storage and intelligent traceability management of electronic archives, characterized in that: Includes the following steps: S1. Collect the original data of the electronic archives, including the archive content data and its associated metadata, wherein the metadata includes at least the creation timestamp and the creator identifier; S2. Perform hash calculation and digital signature processing on the original data to generate blockchain encapsulated data containing the file hash value and signature; S3. Write the blockchain-encapsulated data into a distributed blockchain network and generate an immutable evidence record through a consensus mechanism; S4. Monitor electronic record operation events in real time and generate monitoring alarms when abnormal access and modification behaviors are detected; S5. Based on the monitoring alarm, trigger the smart contract to automatically extract relevant evidence records and generate traceability instructions; S6. Query historical data of the blockchain through the smart contract to obtain the operation timeline and operator information associated with the abnormal event; S7. Analyze historical operation data and generate a reliable traceability report, which includes anomaly markers and operation chain verification results.

2. The blockchain-based method for trusted storage and intelligent traceability management of electronic archives according to claim 1, characterized in that: S1 includes the following steps: S11. Collect user-uploaded archive content data through the electronic archive management system interface. The archive content data formats include PDF, DOC and JPG, and an encrypted transmission protocol is used to ensure data security. S12. Automatically extract archive metadata through the system log module. The archive metadata includes creation timestamp, creator digital certificate and archive category label. The creation timestamp is synchronized with global standard time based on NTP protocol.

3. The blockchain-based method for trusted storage and intelligent traceability management of electronic archives according to claim 1, characterized in that: S2 includes the following steps: S21. Input the archive content data and the archive metadata into the hash algorithm generation unit, and use the SHA-256 algorithm to calculate the archive hash value; S22. Based on the file hash value and the creator's digital certificate, perform digital signature processing and generate a digital signature using RSA encryption technology; S23. Construct a blockchain encapsulated data format, including a hash value field, a signature field, and a metadata index field, wherein the format is JSON and Protobuf structure.

4. The blockchain-based method for trusted storage and intelligent traceability management of electronic archives according to claim 1, characterized in that: S3 includes the following steps: S31. Obtain the blockchain encapsulated data; S32. Send the blockchain-encapsulated data to a blockchain network node, wherein the blockchain network is Ethereum and Hyperledger Fabric, and pay gas fees to confirm the transaction; S33. The blockchain network generates a storage block, including the block hash, timestamp, and transaction ID, and broadcasts it to all nodes to generate a blockchain storage record.

5. The blockchain-based method for trusted storage and intelligent traceability management of electronic archives according to claim 1, characterized in that: S4 includes the following steps: S41. Deploy the file monitoring agent to capture operation event data, including operation frequency. and operation interval time ; S42. A threshold comparison algorithm is used to determine abnormal events. The formula is as follows: , in: This indicates the operating frequency, measured in Hz, and is defined as the number of operations per second. This indicates a preset frequency threshold, in Hz, with a typical value of 10Hz, used to detect abnormal high-frequency access. The interval between operations is expressed in seconds and is defined as the time difference between consecutive operations. This represents a preset time threshold, in seconds (s), with a typical value of 0.5 seconds, used to detect abnormal modifications at short intervals. When the formula conditions are met, a monitoring alarm is generated.

6. The blockchain-based method for trusted storage and intelligent traceability management of electronic archives according to claim 1, characterized in that: S5 includes the following steps: S51. When the monitoring alarm marks an abnormal event, extract the relevant blockchain evidence records; S52. Construct a traceability trigger instruction, including an abnormal event ID, an archive hash, and a traceability range parameter, wherein the traceability range parameter defines a query time window; S53. Input the traceability trigger instruction into the smart contract interface to trigger the execution of the smart contract.

7. The blockchain-based method for trusted storage and intelligent traceability management of electronic archives according to claim 1, characterized in that: S6 includes the following steps: S61. The smart contract parses the traceability trigger instruction and accesses the blockchain network to query historical transactions; S62. Retrieve all relevant operation records based on the archive hash index, including creation, modification, and access events; S63. Filter operation records to generate archive history traceability data, wherein the data format is a time series dataset.

8. The blockchain-based method for trusted storage and intelligent traceability management of electronic archives according to claim 1, characterized in that: S7 includes the following steps: S71. Import historical operation data into the analysis engine and calculate the similarity of operation sequences; S72. Identify abnormal patterns using a similarity calculation formula, which is as follows: in: This represents the similarity of the operation sequences, with a value range of [0,1], where 1 indicates a perfect match. The size of the data in the i-th operation is represented in bytes (B), and is defined as the number of bytes in the file involved in the operation. This represents the average size of historical data, in bytes (B), calculated based on historical records. This represents the standard deviation of the data size, in units of bytes (B), and is a normalized dimensionless quantity. Indicates the length of the operation sequence; when When this happens, mark it as an outlier; S73. The output report includes similarity analysis results.

9. The blockchain-based method for trusted storage and intelligent traceability management of electronic archives according to claim 1, characterized in that: The smart contract in S6 is written in Solidity and includes a traceability logic function and an authorization verification function. The traceability logic function defines the query rules, and the authorization verification function ensures that only authorized users can trigger the traceability.

10. A blockchain-based trusted storage and intelligent traceability management system for electronic archives, implementing the blockchain-based trusted storage and intelligent traceability management method for electronic archives as described in any one of claims 1-9, characterized in that: The system includes a data acquisition and packaging module, a blockchain evidence storage module, and an intelligent traceability management module. The data acquisition and packaging module includes an archive content acquisition unit, a metadata extraction unit, and a data packaging unit; The document content acquisition unit acquires electronic document content data through a system interface; the metadata extraction unit automatically extracts document metadata; and the data encapsulation unit generates blockchain encapsulated data based on the document content data and metadata. The blockchain evidence storage module includes a transaction submission unit, a block generation unit, and an evidence storage unit. The transaction submission unit sends the blockchain-encapsulated data to the blockchain network; The block generation unit processes blockchain transactions to generate evidence-based blocks. The evidence storage unit stores blockchain evidence records; The intelligent traceability management module includes a status monitoring unit, a traceability triggering unit, a historical query unit, and a report generation unit; The status monitoring unit monitors the status of electronic files in real time and detects abnormal events; the traceability triggering unit generates traceability triggering instructions based on abnormal events; the historical query unit calls the smart contract to query historical operation records; and the report generation unit analyzes historical traceability data and outputs a reliable traceability report.

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