Block chain database data management system for traceability application

Abstract

The invention discloses a traceability application-oriented block chain database data management system, particularly relates to the technical field of block chain database data management, and is used for solving the problems of easy data tampering and low verification efficiency caused by traceability data logic association and physical storage splitting. The method comprises the following steps: firstly, matching a parent physical sector offset through an association analysis module, determining a storage partition, and assembling a write-in instruction; then, a topology binding module executes a disk write operation, synchronously reads parent node hash and performs combinatorial operation in combination with a physical address to generate a topology binding check value bound with the physical position; the aggregation anchoring module uses a Merkel tree aggregation check value to generate a root fingerprint and perform uplink, and establishes an anchoring voucher; and finally, a path verification module positions a physical position according to the certificate, executes reverse recursive addressing and step-by-step Hash recalculation, and assembles a pedigree verification packet, so that a closed-loop trust system from physical storage to chain certificate storage is constructed, and the tamper-proof capability and verification efficiency of the traceability data are improved.

Description

A blockchain database data management system for traceability applications Technical Field

[0001] This invention relates to the field of blockchain database data management technology, specifically a blockchain database data management system for traceability applications. Background Technology

[0002] With the deep integration of modern supply chain systems and IoT technology, massive amounts of data are generated throughout the entire lifecycle of goods, from raw material procurement and production to logistics and transportation. This data forms the foundation for traceability applications, requiring the ability to accurately reconstruct the operational history and status of each link to ensure transparency and traceability. In large-scale commercial applications, traceability systems need to process data characterized by high-concurrency writes, strong temporal correlations, and extremely high requirements for data integrity. This makes the management capabilities of the underlying database a key support for the entire credit system.

[0003] However, existing database management methods have substantial technical flaws when handling such traceability data. Traditional relational databases or key-value databases primarily rely on logical indexes (such as primary key IDs) to maintain relationships between data. This logical relationship is completely decoupled from the underlying physical storage location. In actual operation, physical sector data on the storage medium may be directly tampered with or replaced by underlying tools, and the upper-level logical index cannot detect such physical changes in real time, resulting in the data losing its tamper-proof capability at the physical storage level. Furthermore, existing blockchain integration solutions typically only upload the hash value of the data to the chain. When verifying traceability data along a long chain, the system must perform multiple discrete logical queries in a massive database to reconstruct the chain. This frequent random I / O operation leads to low verification efficiency, making it difficult to meet the extremely high real-time requirements of traceability verification scenarios. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a blockchain database data management system for traceability applications, which solves the problems mentioned in the background.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a blockchain database data management system for traceability applications, comprising the following modules: a relational parsing module, used to parse the parent transaction identifier carried in the traceability business data stream, traverse and match the parent physical sector offset corresponding to the parent transaction identifier in the local index, determine the target storage partition of the current data based on the timestamp and spatial characteristic parameters of the traceability business data stream, and assemble a write instruction package containing the parent physical sector offset and the target storage partition; a topology binding module, used to execute the disk sector write operation corresponding to the write instruction package, synchronously read the parent node hash value stored in the parent physical sector offset during the write operation, execute a position-dependent hash algorithm, and combine the parent node hash value and the parent physical sector offset. The system combines the current data content with the data to generate a topology binding verification value. The aggregation and anchoring module caches the topology binding verification value, uses a Merkle tree algorithm to hierarchically aggregate multiple topology binding verification values ​​within a preset time window, calculates the root node state fingerprint, initiates a blockchain-based notarization transaction based on the root node state fingerprint, parses the block header data from the blockchain network to extract the block height and transaction hash, and establishes and stores the anchoring certificate. The path verification module locates the physical disk location corresponding to the topology binding verification value based on the anchoring certificate. It performs reverse recursive addressing using the parent physical sector offset stored at the physical disk location, recalculates and compares the hash consistency of data blocks on the physical path during the addressing process, and assembles a genealogical verification package containing complete physical pointer path data and the anchoring certificate.

[0006] Furthermore, the specific process of parsing the parent transaction identifier carried in the traceability business data stream and traversing the local index to match the parent physical sector offset corresponding to the parent transaction identifier is as follows: The protocol header of the traceability business data stream is stripped using a bitstream analyzer, the metadata fields in the data packet header are identified, and the hash value representing the preceding association is extracted as the parent transaction identifier; the parent transaction identifier is used as the search key to access the key-value pair mapping table residing in memory, and a binary search algorithm is executed to locate the logical block address index entry that matches the search key; the physical cylinder number, head number, and sector number recorded in the logical block address index entry are read, and the physical cylinder number, head number, and sector number are concatenated into binary bits to generate the parent physical sector offset.

[0007] Furthermore, based on the timestamps and spatial characteristic parameters of the traceability business data stream, the target storage partition of the current data is determined, and the specific process of assembling a write instruction packet containing the parent physical sector offset and the target storage partition is as follows: The generation timestamps and geospatial coordinate data in the traceability business data stream are extracted, and the continuous timestamps and geospatial coordinates are mapped into discrete grid codes using a spatiotemporal grid quantization algorithm; the grid codes are input into a consistent hash ring model to calculate the mapping nodes, and the physical volume identifier corresponding to the mapping nodes is determined as the target storage partition; a write operation instruction frame is constructed in memory, the target storage partition is written into the target address field of the write operation instruction frame, and the parent physical sector offset is written into the reference address field; the payload content of the traceability business data stream is serialized and encoded, and filled into the data payload segment of the write operation instruction frame to generate the write instruction packet.

[0008] Furthermore, the topology binding module includes the following steps: parsing the write instruction packet to obtain the target storage partition information, requesting a write mutex lock for the target sector from the disk controller, and locking the input / output channel of the target physical sector; sending a direct memory access read request to the address pointed to by the offset of the parent physical sector through the input / output channel, and reading the data stored in the header of the parent sector as the hash value of the parent node; constructing a hash calculation buffer, filling in the binary source code of the parent node hash value, the offset of the parent physical sector, and the binary encoding sequence of the current data content in a preset order to form a mixed data block; calling a secure hash function to perform iterative calculation on the mixed data block, generating a fixed-length digest string as the topology binding verification value, and appending the topology binding verification value to the header of the current data.

[0009] Furthermore, the specific process of calculating the root node state fingerprint by caching topology binding verification values ​​and using the Merkle tree algorithm to perform hierarchical aggregation of multiple topology binding verification values ​​within a preset time window is as follows: A circular buffer is allocated in volatile memory, and the generated topology binding verification values ​​are pushed into the tail of the queue in chronological order. The queue length and time threshold are checked. When the preset threshold is triggered, the current write pointer of the circular buffer is locked, the topology binding verification values ​​in the queue are copied to the computation memory area, and the original queue is cleared and reset. A pairwise secure hash algorithm is performed on the topology binding verification values ​​in the computation memory area to generate a hash sequence of the parent node at the next higher level. If the total number of nodes at the current level is odd, the last node is padded with bytes before participating in the calculation. The pairwise secure hash algorithm is recursively executed until the generated hash sequence contains only a unique top-level hash value, which is then marked as the root node state fingerprint of the current batch.

[0010] Furthermore, the specific process of initiating a blockchain-based notarized transaction based on the root node state fingerprint, extracting the block height and transaction hash from the block header data fed back by the blockchain network, and establishing and storing the anchor certificate is as follows: Construct a transaction structure conforming to the blockchain smart contract interface specification; fill the data payload field of the transaction structure with the root node state fingerprint; and digitally sign the transaction structure using the private key; broadcast the signed transaction structure to the blockchain peer-to-peer network via a remote procedure call interface, polling the transaction pool status until a confirmation receipt is received; parse the block header information in the confirmation receipt, extract the block height, block hash, and transaction index value; serialize and encapsulate the block height, block hash, and transaction index value with the root node state fingerprint to generate the anchor certificate; and write the anchor certificate as the value, with the root node state fingerprint in the transaction structure as the key, into the key-value pair database of the local metadata management area.

[0011] Furthermore, based on the anchor certificate, the physical disk location corresponding to the topology binding verification value is located. The specific process of performing reverse recursive addressing using the parent physical sector offset stored in the physical disk location is as follows: Read the root node status fingerprint in the anchor certificate, retrieve the batch index table corresponding to the root node status fingerprint in the local metadata management area, and obtain the physical sector address of the last written data in the corresponding batch as the backtracking entry; control the disk read / write head to move to the physical sector corresponding to the backtracking entry, and read the parent physical sector offset stored in the physical sector header metadata area; establish a recursive stack, push the physical sector address onto the stack, and set the read parent physical sector offset as the target address for the next round of addressing; repeatedly execute the head movement and offset reading operations until the read parent physical sector offset is a null pointer, completing the reverse traversal of the entire physical storage chain.

[0012] Furthermore, the specific process of assembling a genealogical verification package containing complete physical pointer path data and anchor credentials by recalculating and comparing the hash consistency of data blocks on the physical path during the addressing process is as follows: During the reverse recursive addressing process, the data content stored in the traversed physical sectors is separated from the topology binding verification value in the metadata header; the physical address parameters of the current physical sector and the offset of the parent physical sector are extracted, and the position-dependent hash algorithm used to generate the topology binding verification value is called in combination with the data content to calculate the recalculated hash value; the recalculated hash value is compared with the topology binding verification value extracted from the metadata header in binary consistency. If the comparison is consistent, the data content and physical address parameters are added to the verification result set; after all nodes are compared, the Merkle tree verification path corresponding to the anchor credentials is reconstructed, and the verification result set, the Merkle tree verification path and the anchor credentials are packaged to generate the genealogical verification package.

[0013] The present invention has the following beneficial effects: (1) A blockchain database data management system for traceability applications, through the cooperation of the association resolution module and the topology binding module, realizes the forced binding of data logical lineage and physical storage location. When writing data, the system does not simply rely on the logical ID, but forcibly reads the physical sector offset of the parent data and incorporates this physical address parameter into the hash calculation process of the current data. This position-dependent hash algorithm makes the relationship between data form a linked list-like entity structure at the physical disk level. Any move, copy or sector replacement operation on the underlying physical file will cause the physical offset to change, thereby making the hash verification invalid. This mechanism effectively prevents attacks that bypass the database engine and directly tamper with the underlying physical file. At the same time, it uses spatiotemporal feature parameters to determine the target partition, optimizes the physical distribution of heterogeneous traceability data, and improves writing performance.

[0014] (2) A blockchain database data management system for traceability applications establishes a trusted channel from the physical sectors of the disk directly to the blockchain ledger through the collaboration of an aggregation anchoring module and a path verification module. The aggregation anchoring module gathers hash values ​​with physical location constraints and uploads them to the chain, establishing a physical storage state fingerprint at a specific point in time. During the verification phase, the path verification module uses physical sector offsets for reverse recursive addressing. This physical pointer-based addressing method transforms traditional database logical lookups into sequential disk read operations, significantly reducing I / O overhead. Simultaneously, during the backtracking process, hashes are recalculated and compared level by level, allowing users to complete self-verification and verification of the entire traceability chain without downloading the entire database, relying solely on anchor credentials and physical pointer paths. This greatly improves the efficiency and reliability of data integrity verification.

[0015] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0016] Figure 1 is a flowchart of a blockchain database data management system for traceability applications according to the present invention. Detailed Implementation

[0017] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0018] This application provides a blockchain database data management system for traceability applications, which solves the technical problems of data being easily tampered with at the underlying level due to the separation of logical indexes and physical storage in existing traceability databases, as well as the high I / O overhead and low efficiency during cross-chain verification.

[0019] The overall approach of the scheme in this application embodiment is as follows: First, during the data writing phase, the system converts the logical parent-child transaction relationship into a physical sector pointing relationship on the disk by parsing the physical storage address of the preceding data. Next, during the write operation, a position-dependent hash algorithm is used to encrypt and bind the parent physical address, the parent content hash, and the current data, so that the data forms an indivisible causal chain at the physical level. Subsequently, the system periodically aggregates these hash fingerprints bound to physical attributes and uploads them to the blockchain to generate an immutable anchor certificate. Finally, during the query and verification phase, the system directly locates the physical location based on the anchor certificate, quickly backtracks along the physical pointer, and recalculates and verifies, thereby achieving efficient and reliable physical-level data traceability and integrity proof.

[0020] Please refer to Figure 1. This embodiment of the invention provides a technical solution: a blockchain database data management system for traceability applications, comprising the following modules: a relational parsing module, used to parse the parent transaction identifier carried in the traceability business data stream, traverse and match the parent physical sector offset corresponding to the parent transaction identifier in the local index, determine the target storage partition of the current data based on the timestamp and spatial characteristic parameters of the traceability business data stream, and assemble a write instruction package containing the parent physical sector offset and the target storage partition; a topology binding module, used to execute the disk sector write operation corresponding to the write instruction package, synchronously read the parent node hash value stored in the parent physical sector offset during the write operation, execute a position-dependent hash algorithm, and combine the parent node hash value, parent physical sector offset, and the current data... The preceding data content is combined and processed to generate a topology binding verification value. The aggregation and anchoring module is used to cache the topology binding verification value. It performs hierarchical aggregation of multiple topology binding verification values ​​within a preset time window using the Merkle tree algorithm to calculate the root node state fingerprint. Based on the root node state fingerprint, a blockchain notarization transaction is initiated. The block header data fed back by the blockchain network is parsed to extract the block height and transaction hash, and an anchoring certificate is established and stored. The path verification module is used to locate the physical disk location corresponding to the topology binding verification value according to the anchoring certificate. It performs reverse recursive addressing through the parent physical sector offset stored in the physical disk location. During the addressing process, the hash consistency of the data blocks on the physical path is recalculated and compared level by level. The genealogical verification package containing complete physical pointer path data and anchoring certificate is assembled.

[0021] In this implementation scheme, the system can be based on customized storage controller firmware or kernel-level drivers. The association resolution module is mainly responsible for physical addressing and routing planning before data writing. This module parses the parent transaction identifier carried in the source business data stream, searches in the local index, and maps the logical business relationship to the physical address information on the underlying storage medium. Specifically, this is reflected in the parent physical sector offset, that is, the precise coordinates of the parent data on the disk cylinder, head, and sector. At the same time, this module executes a sharding algorithm based on the timestamp and spatial characteristic parameters to determine the target storage partition of the current data. This process involves discretizing and mapping continuous spatiotemporal data to specific logical volumes or physical disk partitions. The finally assembled write instruction package is a low-level input / output control unit that encapsulates the target physical address, reference physical address, and data payload. Its technical role is to establish a direct pointing relationship between the current data and the previous data at the physical storage level before the data is written to disk, laying the foundation for building a physical-level anti-tampering chain. The topology binding module is the core write execution engine of the system, responsible for establishing physical constraints during the data persistence process. When performing disk sector write operations, this module uses direct memory access technology to synchronously read the sector data pointed to by the parent physical sector offset and extracts the parent node hash value. Based on this, a position-dependent hash algorithm is executed. This is a cryptographic digest generation technique that uses the physical storage address as a necessary parameter. It performs a mixed operation on the parent node hash value, the physical address of the parent data, and the current data content to generate a topology binding verification value. This verification value is essentially a digital fingerprint bound to the storage location attribute. Its technical function is to achieve strong coupling between data content and storage location. Once the data is moved or the physical location of the preceding data changes, the verification value will become invalid, thus effectively preventing direct tampering of the underlying physical sectors by bypassing the file system. The aggregation and anchoring module acts as a trust bridge between off-chain physical storage and on-chain trusted ledger. This module collects topology binding verification values ​​over a period of time through a caching mechanism, constructs a hash binary tree structure using the Merkle tree algorithm, and performs hierarchical aggregation operations on a large number of discrete verification values. The resulting root node state fingerprint is a unique cryptographic digest representing the physical state of all data within that time window. Subsequently, the module initiates a blockchain-based notarization transaction based on this fingerprint, parses the returned block header data, and extracts the block height and transaction hash to generate an anchored credential. The technical advantage of this process lies in compressing massive amounts of underlying physical storage data into minimal on-chain evidence. This solves the blockchain storage bottleneck while leveraging the blockchain's immutability to lock the physical topology state of the off-chain database at a specific moment. The path verification module is used to perform efficient data verification and backtracking based on physical pointers.This module locates the physical disk position at the end of the data chain based on the index information in the anchor credential. It then performs reverse recursive addressing using the parent physical sector offset stored at the disk position. This is a low-level reading mechanism similar to traversing nodes backward using pointers in a linked list data structure. During the addressing process, the module not only reads data but also recalculates the hash value of each node in real time and compares it with the stored checksum. The final assembled genealogy verification package contains complete physical pointer path data and on-chain anchor credentials. Its technical advantage lies in transforming complex logical association queries into efficient sequential disk read operations and providing a complete self-verifying evidence chain containing data content, physical location path, and on-chain timestamps, significantly improving the verification efficiency and credibility of traceability data.

[0022] Specifically, the process of parsing the parent transaction identifier carried in the traceability business data stream and traversing the local index to match the parent physical sector offset corresponding to the parent transaction identifier is as follows: The protocol header of the traceability business data stream is stripped using a bitstream analyzer, the metadata fields in the data packet header are identified, and the hash value representing the preceding association is extracted as the parent transaction identifier; the parent transaction identifier is used as the search key to access the key-value pair mapping table residing in memory, and a binary search algorithm is executed to locate the logical block address index entry that matches the search key; the physical cylinder number, head number, and sector number recorded in the logical block address index entry are read, and the physical cylinder number, head number, and sector number are concatenated into binary bits to generate the parent physical sector offset.

[0023] In this implementation scheme, parsing the parent transaction identifier carried in the traceability business data stream and locating the physical sector offset is a crucial step in mapping logical traceability relationships to physical storage addresses. Specifically, the system first uses a bitstream analyzer to unpack the input binary data stream at the protocol level. This step identifies specific frame header sequences to strip off protocol control information, directly locating the metadata fields in the data payload area, and extracting a predefined length hash sequence as the parent transaction identifier. Subsequently, the system uses this parent transaction identifier as the search key to perform a lookup operation in the key-value pair mapping table maintained in memory. This mapping table uses a pre-sorted storage structure, so the system executes a binary search algorithm to quickly locate the logical block address index entry that matches the search key by continuously narrowing the search interval. This index entry stores the three-dimensional geometric coordinates of the data on the hard disk, namely the cylinder number, head number, and sector number. To convert the above three-dimensional geometric coordinates into linear addressing parameters that the disk controller can directly recognize, the system performs binary bit concatenation operations on the physical parameters. This process combines independent geometric parameters into a unique linear integer through bitwise operations, and the calculation formula is as follows: The parameters are explained as follows: The generated parent physical sector offset is a 64-bit unsigned integer used to uniquely identify the physical storage location on the disk. The physical cylinder number recorded in the logical block address index entry indicates the track location where the data is located; The head number recorded in the logical block address index entry indicates the disk surface where the data is located; The sector number recorded in the logical block address index entry indicates the specific sector segment of the data on the track; The number of bits used by the head number parameter is determined by the disk formatting parameters; The number of binary bits used by the sector number parameter; The binary left shift operator is used to move the parameter to the corresponding high-order bit range. Through the above calculation, the system merges the scattered CHS (cylinder-head-sector) physical coordinates into a single linear address, which directly corresponds to the physical address space at the disk's underlying layer, providing a precise target pointer for subsequent fast / O reads.

[0024] Specifically, the process of determining the target storage partition of the current data based on the timestamp and spatial characteristic parameters of the traceability business data stream, and assembling a write instruction packet containing the parent physical sector offset and the target storage partition is as follows: Extract the generation timestamp and geospatial coordinate data from the traceability business data stream, and use a spatiotemporal grid quantization algorithm to map continuous timestamps and geospatial coordinates into discrete grid codes; input the grid codes into a consistent hash ring model to calculate the mapping nodes, and determine the physical volume identifier corresponding to the mapping nodes as the target storage partition; construct a write operation instruction frame in memory, write the target storage partition into the target address field of the write operation instruction frame, and write the parent physical sector offset into the reference address field; serialize and encode the payload content of the traceability business data stream, fill it into the data payload segment of the write operation instruction frame, and generate a write instruction packet.

[0025] In this implementation scheme, the process of determining the target storage partition based on spatiotemporal characteristic parameters and assembling and writing instruction packets aims to solve the load balancing and efficient routing problem of massive heterogeneous tracing data. Specifically, the system first extracts and generates timestamps and geospatial coordinate data (longitude and latitude) from the tracing business data stream. In order to map continuous and infinite spatiotemporal data to limited storage resources, the system adopts a spatiotemporal grid quantization algorithm to divide the time and space dimensions into discrete grid cells. The formula for calculating the grid encoding is as follows: The parameters are explained as follows: The calculated discrete grid code is used to characterize the clustering features of the data in the spatiotemporal dimension; The generation timestamp in the traceability business data stream; The system's preset start reference time; A preset time quantization step size, for example, set to 3600 seconds, is used to aggregate time into discrete slots at the hour level; Lat, Latitude and longitude values ​​in geospatial coordinates; , Preset geographic coordinate origin; The preset spatial quantization step size is used to divide the side length of the geographic grid; , , These are the weighting coefficients for the time dimension, latitude dimension, and longitude dimension, respectively. The method for determining these three coefficients is as follows: count the query frequency of each dimension in the historical query log, normalize the frequency and use it as the weight value of the corresponding dimension. The dimension with higher query frequency is assigned a larger weight to ensure the clustering of hot data in storage. The floor operation. After obtaining the grid code, in order to achieve uniform data distribution in a distributed storage environment, the system inputs the grid code into a consistent hash ring model. This process maps the grid code to the virtual ring space through hash operations and finds the nearest virtual node in a clockwise direction. The calculation logic is as follows: The parameters are explained as follows: : Determine the physical volume identifier corresponding to the mapping node, i.e., the target storage partition; The hash value corresponding to the kth virtual node on the consistent hash ring; A non-cryptographic high-speed hash function, such as MurmurHash, is used to ensure the discreteness of the mapping; The total space size of a hash ring is usually taken as After determining the target storage partition through the above steps, the system allocates an instruction buffer in memory and constructs a write operation instruction frame according to the specifications of the underlying I / O controller. The system fills the target address field of the instruction frame with the calculated physical volume identifier, fills the reference address field with the parent physical sector offset generated in the previous steps, and fills the data segment with the serialized and encoded data payload, finally generating a complete write instruction packet. This process ensures that data is written while adhering to a load-balanced partitioning strategy and preserving the physical lineage.

[0026] Specifically, the topology binding module includes the following steps: parsing the write instruction packet to obtain the target storage partition information, requesting a write mutex lock for the target sector from the disk controller, and locking the input / output channel of the target physical sector; sending a direct memory access read request to the address pointed to by the parent physical sector offset through the input / output channel, and reading the data stored in the parent sector header as the parent node hash value; constructing a hash calculation buffer, filling in the parent node hash value, the binary source code of the parent physical sector offset, and the binary encoding sequence of the current data content in a preset order to form a mixed data block; calling a secure hash function to perform iterative calculations on the mixed data block, generating a fixed-length digest string as the topology binding verification value, and appending the topology binding verification value to the current data header.

[0027] In this implementation scheme, the disk writing and physical constraint binding process performed by the topology binding module is a core step in ensuring that data has tamper-proof capabilities at the underlying physical storage structure. Specifically, this process first involves exclusive control of the underlying input / output channels. After the system parses the write instruction packet to obtain the target storage partition information, it requests a write mutex lock for the target sector from the disk controller. The write mutex lock is a kernel-level synchronization primitive used for concurrency control. Its technical function is to forcibly suspend other processes' read and write access to the target physical sector in a multi-tasking operating system environment, thereby locking the input / output channel of the target physical sector and ensuring that subsequent hash reads and data write operations are atomic, preventing data inconsistencies caused by concurrent contention. After establishing the exclusive channel, the system performs synchronous read operations on the preceding node. The system sends a direct memory access read request to the address pointed to by the offset of the parent physical sector through the input / output channel. Direct memory access, or DMA technology, is a bus control mechanism that allows hardware subsystems to directly read and write system memory without the intervention of the central processing unit. In this step, the DMA controller directly transfers the data block stored at the header of the parent physical sector to memory, and the system extracts the hash value of the parent node from it. This approach significantly reduces the load on the central processing unit and substantially decreases the latency of reading data from preceding nodes, meeting the stringent real-time requirements of write operations. Subsequently, the system enters the core cryptographic computation phase, constructing a hash calculation buffer and generating a topology binding verification value. The system allocates a buffer in a secure memory area and fills it with the extracted parent node hash value, the binary original code of the parent physical sector offset, and the binary encoded sequence of the current data content in a preset order, forming a hybrid data block containing three elements: historical lineage, physical location, and current content. Then, the system calls a secure hash function to iteratively compute this hybrid data block. This computation process is not only a data digest but also a process of solidifying physical location constraints. The calculation formula is as follows: The parameters are explained as follows: The generated topology binding verification value is a fixed-length hexadecimal string used as a unique physical anti-counterfeiting fingerprint for the current data. The multi-round XOR accumulation operator is used to perform bit-level mixing of the hash results of each iteration, enhancing collision resistance. The preset total number of iteration rounds is used to increase the computation time cost to resist brute-force attacks. It is determined by selecting an integer value that can balance write performance and security based on the average disk write latency and security level requirements of the current system, for example, 1024. The index variable for the current iteration round; The secure hash function used, such as the Chinese national cryptographic algorithm SM3 or SHA-256, is used to generate irreversible digital digests; The hash value of the parent node read from the parent sector header; The left shift operator is used to change the bit arrangement of the parent hash value in each iteration, increasing the confusion. The preset displacement step size parameter, for example, is set to 7 bits; Bitwise XOR operator; The binary original code of the parent physical sector offset represents the physical storage coordinates of the preceding data. The location weighting coefficient is usually a large prime number, used to map the linearly growing physical address to discrete weighted values, preventing attackers from exploiting address patterns. Data concatenation operators; The current data content is represented by a binary encoded sequence. Calculated using the formula above, the topology binding checksum generated by the system not only contains information about the data itself but also deeply integrates the physical location information of preceding data. Finally, the system appends this checksum to the header of the current data and writes it to the disk. This series of operations elevates the difficulty of logical data tampering to the physical level. Any unauthorized movement of the underlying physical sectors or replacement of sectors in preceding data will cause the checksum verification to fail due to the change in physical address, thus achieving physical-level traceability security protection.

[0028] Specifically, the process of caching topology binding verification values ​​and calculating the root node state fingerprint by hierarchically aggregating multiple topology binding verification values ​​within a preset time window using the Merkle tree algorithm is as follows: A circular buffer is allocated in volatile memory, and the generated topology binding verification values ​​are pushed into the tail of the queue in chronological order. The queue length and time threshold are checked. When the preset threshold is triggered, the current write pointer of the circular buffer is locked, the topology binding verification values ​​in the queue are copied to the computation memory area, and the original queue is cleared and reset. A pairwise secure hash algorithm is performed on the topology binding verification values ​​in the computation memory area to generate a hash sequence of the parent node at the next higher level. If the total number of nodes at the current level is odd, the last node is padded with bytes before participating in the calculation. The pairwise secure hash algorithm is recursively executed until the generated hash sequence contains only a unique top-level hash value, which is then marked as the root node state fingerprint of the current batch.

[0029] In this implementation scheme, the process of caching topology binding verification values ​​and calculating the root node state fingerprint is the core data processing step for achieving offline compression and efficient verification of massive traceability data. Specifically, the system first allocates a circular buffer in volatile memory. A circular buffer is a first-in, first-out (FIFO) data structure with interconnected nodes. Its technical advantage lies in its ability to handle high-concurrency data write streams with extremely low memory overhead, avoiding performance fluctuations caused by frequent memory allocation and release. The system pushes the generated topology binding verification values ​​into a queue in chronological order and sets a dual trigger mechanism: a queue length threshold and a time threshold. When any threshold is triggered, the system performs an atomic lock operation, locking the current write pointer and copying a data snapshot to an independent computation memory area. This ensures that new data writes do not disrupt the consistency of the data being processed during subsequent complex hash aggregation operations. Subsequently, the system enters the core Merkle tree hierarchical aggregation calculation stage. The system pairs the topology binding verification values ​​in the computation memory area. If the total number of nodes is odd, the last node is copied to complete the binary tree structure. The hash aggregation operation at each level follows strict recursive logic, and its calculation formula is as follows: The parameters are explained as follows: : The hash value of the m-th node at level k. When it is the highest level, this value is the final root node state fingerprint; k: The current tree level index, with values ​​increasing from 1 to the top of the tree; The node index position within the current level; The secure hash algorithm function used, such as SHA-3, is used to generate a fixed-length node digest; The hash value of the left child node of the parent node; : The hash value of the right child node of the parent level; The bitwise XOR operator is used to increase the obfuscation of the input. The hierarchical salting factor is determined by taking the combined hash of the current hierarchical index value k and the current time window identifier. The purpose of introducing this factor is to prevent rainbow table attacks and ensure that even if two batches contain the same dataset, the generated intermediate node hashes will be completely different due to the different hierarchical factors. Binary data concatenation operator. Through the above recursive operation, until a unique top-level hash value is generated, the system marks it as the root node state fingerprint of the current batch. This process compresses the integrity status of thousands of traceability data points into a fingerprint of a few tens of bytes, greatly reducing the cost of subsequent blockchain storage.

[0030] Specifically, the process of initiating a blockchain-based notarized transaction based on the root node state fingerprint, extracting the block height and transaction hash from the block header data fed back by the blockchain network, and establishing and storing the anchor certificate is as follows: Construct a transaction structure conforming to the blockchain smart contract interface specification; fill the data payload field of the transaction structure with the root node state fingerprint; and digitally sign the transaction structure using the private key; broadcast the signed transaction structure to the blockchain peer-to-peer network via a remote procedure call interface, polling the transaction pool status until a confirmation receipt is received; parse the block header information in the confirmation receipt, extract the block height, block hash, and transaction index value; serialize and encapsulate the block height, block hash, and transaction index value with the root node state fingerprint to generate the anchor certificate; and write the anchor certificate as the value, using the root node state fingerprint in the transaction structure as the key, into the key-value pair database of the local metadata management area.

[0031] In this implementation plan, the process of initiating a notarized transaction based on the root node state fingerprint and establishing an anchored certificate is a crucial step in achieving trusted mutual recognition between off-chain data and the on-chain ledger. Specifically, the system first constructs a transaction structure that conforms to the blockchain smart contract interface specification. This structure is a standard data container for value transfer or state change in the blockchain network. The system fills the data payload field with the root node state fingerprint calculated in the previous steps, making it immutable evidence permanently stored in the blockchain ledger. To ensure the legality and non-repudiation of the transaction, the system uses the private key to digitally sign the transaction structure. This process involves the core calculations of an asymmetric encryption algorithm, and the calculation logic for signature generation is as follows: The parameters are explained as follows: The generated digital signature data is used by network nodes to verify the identity of the transaction initiator. The selected elliptic curve digital signature algorithm, such as ECDSA or Ed25519; The user's private key is stored in the local security module; A preprocessing hash function is used to compress transaction data of arbitrary length into a fixed-length message digest for signing purposes; :Transaction data payload containing the root node state fingerprint; The timestamp of the transaction creation is used to prevent replay attacks. A random number or counter is used to ensure the uniqueness of the transaction hash. After signing, the system broadcasts the transaction to the blockchain peer-to-peer network via a remote procedure call interface and initiates a polling mechanism to monitor the transaction pool status. Once a confirmation receipt is received, the system parses the block header information, extracting the block height, block hash, and transaction index value. This information constitutes the spatiotemporal coordinates of the data on the blockchain. Finally, the system performs serialization encapsulation, combining the above coordinate information with the root node state fingerprint to generate an anchored credential, and writes it to the local metadata database in key-value pairs. The advantage of this is that subsequent queries do not require traversing the entire blockchain; the on-chain evidence location can be quickly obtained using the local high-speed key-value index, achieving millisecond-level retrieval of evidence data.

[0032] Specifically, the process of locating the physical disk location corresponding to the topology binding verification value based on the anchoring certificate, and performing reverse recursive addressing using the parent physical sector offset stored in the physical disk location is as follows: Read the root node status fingerprint in the anchoring certificate, retrieve the batch index table corresponding to the root node status fingerprint in the local metadata management area, and obtain the physical sector address of the last written data in the corresponding batch as the backtracking entry; control the disk read / write head to move to the physical sector corresponding to the backtracking entry, and read the parent physical sector offset stored in the metadata area at the head of the physical sector; establish a recursive stack, push the physical sector address onto the stack, and set the read parent physical sector offset as the target address for the next round of addressing; repeatedly execute the head movement and offset reading operations until the read parent physical sector offset is a null pointer, completing the reverse traversal of the entire physical storage chain.

[0033] In this implementation scheme, the process of locating the physical location based on the anchored credential and performing reverse recursive addressing is a crucial step in transforming the logical trust root on the blockchain into the underlying physical access path of the disk. Specifically, the system first parses the root node state fingerprint in the anchored credential and uses it as an index key to retrieve data from the batch index table maintained in the local metadata management area. The batch index table is a B+ tree or hash table structure that records the mapping relationship between hash fingerprints and physical storage intervals. The system retrieves the physical sector address corresponding to the last write operation in the batch of data, i.e., the backtracking entry point. Subsequently, the system controls the disk drive to perform a physical addressing operation, driving the read / write head to move to the cylinder and sector where the backtracking entry point is located, and reads the parent physical sector offset stored in the metadata area at the head of that physical sector. To completely reconstruct the time sequence of data writing, the system establishes a recursive stack in memory. The recursive stack is a last-in-first-out data structure used to temporarily store node information on the backtracking path. The system pushes the current physical sector address onto the stack and sets the read parent physical sector offset as the target address for the next round of addressing. The logical state transition of this recursive addressing process can be represented by the following formula: The parameters are explained as follows: The target physical address corresponding to the next recursion depth d+1, i.e., the location of the parent sector; : Sector metadata read function, used to directly access the low-level interface of the disk controller to obtain control information in the sector header; The metadata structure defined in the sector header contains a pointer field pointing to the previous node; : The physical sector address at the current recursion depth d; The push assignment operator means that the current address is stored in the recursive stack; The recursive stack's storage unit at depth d is used to pop data sequentially during subsequent verification phases. The system repeatedly executes the above head movement and metadata reading operations, continuously backtracking to earlier time nodes until the parent physical sector offset read is all zeros or a specific null pointer identifier, indicating that the starting node of the tracing link has been reached, thus completing the reverse traversal of the entire physical storage chain.

[0034] Specifically, the process of recalculating and comparing the hash consistency of data blocks on the physical path during the addressing process, and assembling the genealogical verification package containing complete physical pointer path data and anchor credentials is as follows: During the reverse recursive addressing process, the data content stored in the traversed physical sectors is separated from the topology binding verification value in the metadata header; the physical address parameters of the current physical sector and the offset of the parent physical sector are extracted, and the position-dependent hash algorithm used to generate the topology binding verification value is called in combination with the data content to calculate the recalculated hash value; the recalculated hash value is compared with the topology binding verification value extracted from the metadata header in binary consistency. If the comparison is consistent, the data content and physical address parameters are added to the verification result set; after all nodes are compared, the Merkle tree verification path corresponding to the anchor credentials is reconstructed, and the verification result set, the Merkle tree verification path and the anchor credentials are packaged to generate the genealogical verification package.

[0035] In this implementation scheme, the process of recalculating hashes and assembling lineage verification packets at each level during addressing is the core step in achieving self-verification of data integrity. Specifically, while performing the aforementioned reverse recursive addressing, the system performs a separation operation on each traversed physical sector, stripping the stored user data content from the topology binding checksum in the metadata header. To verify that the data has not been physically modified during storage, the system extracts the physical address parameters (cylinder, head, sector number) of the current physical sector and the offset of the parent physical sector, and combines this with the separated data content to re-invoke the position-dependent hash algorithm used when generating the topology binding checksum. This recalculation and comparison process is implemented through a bit-level consistency check function, the calculation logic of which is as follows: The parameters are explained as follows: The Boolean verification result, if true, indicates that the current data block and its physical location have not been tampered with; The logical NOT operator is used to reverse the cumulative difference result into a validity flag; The multi-bit logical OR operator is used to check the comparison result of all bits; if even one bit is inconsistent, the overall result is false. The binary bit length of the hash digest, for example, 256 bits; The current binary bit index being compared; The b-th bit of the original topology binding check value extracted from the physical sector metadata header; The bitwise XOR operator returns 0 if the two compared bits are the same, and 1 if they are different. The system's default position-dependent hash algorithm function is consistent with the algorithm used during writing; The raw data content read from the sector; The physical address parameter of the current sector, reflecting the current location constraints; The parent physical sector offset extracted from metadata, reflecting lineage location constraints; Data concatenation operator. If the above comparison results match, the system adds the data block and its physical address information to the verification result set. After all nodes in the entire chain have passed verification, the system reconstructs the corresponding Merkle tree verification path based on the index information in the anchor certificate. Finally, the system serializes and packages the verification result set, the Merkle tree verification path, and the anchor certificate to generate a genealogy verification package. This verification package not only contains complete traceability data but also includes end-to-end evidence from the physical disk to the blockchain ledger, enabling users to independently verify the authenticity of the data.

[0036] In summary, this application has at least the following effects: A blockchain database data management system for traceability applications innovatively maps the logical lineage of business data directly to the physical pointer constraints of the underlying disk through association resolution and topology binding mechanisms. It uses a position-dependent hash algorithm to forcibly bind data content and physical sector addresses, effectively defending against tampering or replacement attacks that bypass the file system to the underlying physical sectors. At the same time, the system combines aggregation anchoring and path verification technologies to establish a trusted channel from the physical disk directly to the blockchain ledger. It uses physical offsets for reverse recursive addressing to transform complex logical association queries into efficient physical sequential read operations, significantly reducing the I / O overhead of retrieving massive traceability data. Furthermore, through real-time recalculation and comparison of on-chain anchored credentials and off-chain physical paths, it achieves highly reliable and low-latency self-certification of traceability data integrity without requiring full database synchronization.

[0037] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0038] This invention is described with reference to flowchart illustrations and / or block diagrams of systems, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in one or more blocks of the flowchart illustrations and / or one or more blocks of the block diagrams.

[0039] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means that implement the functions specified in one or more flowcharts and / or one or more block diagrams.

[0040] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable apparatus, provide steps for implementing the functions specified in one or more flowcharts and / or one or more block diagrams.

[0041] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0042] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A blockchain database data management system for traceability applications, characterized in that, It includes the following modules: the association parsing module, which is used to parse the parent transaction identifier carried in the traceability business data stream, traverse and match the parent physical sector offset corresponding to the parent transaction identifier in the local index, determine the target storage partition of the current data according to the timestamp and spatial feature parameters of the traceability business data stream, and assemble a write instruction package containing the parent physical sector offset and the target storage partition. The topology binding module is used to execute the disk sector write operation corresponding to the write instruction package. During the write operation, it synchronously reads the parent node hash value stored in the parent physical sector offset, executes the position-dependent hash algorithm, and combines the parent node hash value, the parent physical sector offset and the current data content to generate the topology binding verification value. The aggregation and anchoring module is used to cache topology binding verification values. It performs hierarchical aggregation of multiple topology binding verification values ​​within a preset time window using the Merkle tree algorithm, calculates the root node state fingerprint, initiates blockchain notarization transactions based on the root node state fingerprint, parses the block header data fed back by the blockchain network to extract the block height and transaction hash, and establishes and stores anchoring credentials. The path verification module is used to locate the physical disk location corresponding to the topology binding verification value based on the anchor credential. It performs reverse recursive addressing by storing the parent physical sector offset in the physical disk location. During the addressing process, it recalculates and compares the hash consistency of data blocks on the physical path level by level, and assembles a genealogy verification package containing complete physical pointer path data and anchor credential.

2. The blockchain database data management system for traceability applications according to claim 1, characterized in that: The specific process of parsing the parent transaction identifier carried in the traceability business data stream and traversing the local index to match the parent physical sector offset corresponding to the parent transaction identifier is as follows: The protocol header of the traceability business data stream is stripped using a bitstream analyzer, the metadata fields in the data packet header are identified, and the hash value representing the preceding association is extracted as the parent transaction identifier. The parent transaction identifier is used as the search key to access the key-value pair mapping table residing in memory, and a binary search algorithm is executed to locate the logical block address index entry that matches the search key. The physical cylinder number, head number, and sector number recorded in the logical block address index entry are read, and the physical cylinder number, head number, and sector number are concatenated into binary bits to generate the parent physical sector offset.

3. A blockchain database data management system for traceability applications according to claim 1, characterized in that: The specific process of determining the target storage partition of the current data based on the timestamp and spatial characteristic parameters of the traceability business data stream, and assembling a write instruction packet containing the parent physical sector offset and the target storage partition is as follows: Extract the generation timestamp and geospatial coordinate data from the traceability business data stream, and use a spatiotemporal grid quantization algorithm to map continuous timestamps and geospatial coordinates into discrete grid codes; input the grid codes into a consistent hash ring model to calculate the mapping nodes, and determine the physical volume identifier corresponding to the mapping nodes as the target storage partition; construct a write operation instruction frame in memory, write the target storage partition into the target address field of the write operation instruction frame, and write the parent physical sector offset into the reference address field; serialize and encode the payload content of the traceability business data stream, fill it into the data payload segment of the write operation instruction frame, and generate a write instruction packet.

4. A blockchain database data management system for traceability applications according to claim 1, characterized in that: The topology binding module includes the following steps: parsing the write instruction packet to obtain the target storage partition information, requesting a write mutex lock for the target sector from the disk controller, and locking the input / output channel of the target physical sector; sending a direct memory access read request to the address pointed to by the offset of the parent physical sector through the input / output channel, and reading the data stored in the header of the parent sector as the hash value of the parent node; constructing a hash calculation buffer, filling in the binary source code of the parent node hash value, the offset of the parent physical sector, and the binary encoding sequence of the current data content in a preset order to form a mixed data block; calling a secure hash function to perform iterative calculation on the mixed data block, generating a fixed-length digest string as the topology binding check value, and appending the topology binding check value to the header of the current data.

5. A blockchain database data management system for traceability applications according to claim 1, characterized in that: The specific process of calculating the root node state fingerprint by caching topology binding verification values ​​and performing hierarchical aggregation of multiple topology binding verification values ​​within a preset time window using the Merkle tree algorithm is as follows: A circular buffer is opened in volatile memory, and the generated topology binding verification values ​​are pushed into the tail of the queue of the circular buffer in chronological order. The queue length and time threshold are checked. When the preset threshold is triggered, the current write pointer of the circular buffer is locked, the topology binding verification value in the queue is copied to the computation memory area, and the original queue is cleared and reset. Perform a pairwise secure hash algorithm operation on the topology binding check value in the computation memory area to generate the parent node hash sequence of the next level. If the total number of nodes in the current level is odd, perform byte padding on the last node before it participates in the operation. Recursively perform the pairwise secure hash algorithm operation until the generated hash sequence contains only a unique top-level hash value, and mark it as the root node state fingerprint of the current batch.

6. A blockchain database data management system for traceability applications according to claim 1, characterized in that: The specific process of initiating a blockchain-based notarized transaction based on the root node state fingerprint, extracting the block height and transaction hash from the block header data fed back by the blockchain network, and establishing and storing the anchor certificate is as follows: Construct a transaction structure conforming to the blockchain smart contract interface specification; fill the data payload field of the transaction structure with the root node state fingerprint; and digitally sign the transaction structure using the private key; broadcast the signed transaction structure to the blockchain peer-to-peer network via a remote procedure call interface, polling the transaction pool status until a confirmation receipt is received; parse the block header information in the confirmation receipt, extract the block height, block hash, and transaction index value; serialize and encapsulate the block height, block hash, and transaction index value with the root node state fingerprint to generate the anchor certificate; The anchored credential is used as the value, and the root node state fingerprint in the transaction structure is used as the key. The data is written to the key-value pair database in the local metadata management area.

7. A blockchain database data management system for traceability applications according to claim 1, characterized in that: The specific process of locating the physical disk location corresponding to the topology binding verification value based on the anchoring certificate and performing reverse recursive addressing through the parent physical sector offset stored in the physical disk location is as follows: Read the root node status fingerprint in the anchoring certificate, retrieve the batch index table corresponding to the root node status fingerprint in the local metadata management area, and obtain the physical sector address of the last written data in the corresponding batch as the backtracking entry; control the disk read / write head to move to the physical sector corresponding to the backtracking entry, and read the parent physical sector offset stored in the physical sector header metadata area; Establish a recursive stack, push the physical sector address onto the stack, and set the read parent physical sector offset as the target address for the next round of addressing; repeatedly execute head movement and offset reading operations until the read parent physical sector offset is a null pointer, thus completing the reverse traversal of the entire physical memory chain.

8. A blockchain database data management system for traceability applications according to claim 1, characterized in that: The specific process of assembling a genealogical verification package containing complete physical pointer path data and anchor credentials by recalculating and comparing the hash consistency of data blocks on the physical path during the addressing process is as follows: During the reverse recursive addressing process, the data content stored in the traversed physical sectors is separated from the topology binding verification value in the metadata header; the physical address parameters of the current physical sector and the offset of the parent physical sector are extracted, and the position-dependent hash algorithm used to generate the topology binding verification value is called in combination with the data content to calculate the recalculated hash value; the recalculated hash value is compared with the topology binding verification value extracted from the metadata header in binary consistency. If the comparison is consistent, the data content and physical address parameters are added to the verification result set; after all nodes are compared, the Merkle tree verification path corresponding to the anchor credentials is reconstructed, and the verification result set, the Merkle tree verification path and the anchor credentials are packaged to generate the genealogical verification package.

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