Blockchain-based digital economy e-commerce management method and system

Abstract

The application relates to the technical field of blockchains, in particular to a digital economic e-commerce management method and system based on a blockchain, which comprises the following steps: acquiring order data, extracting commodity codes, transaction amounts, addresses of both parties, splicing, executing SHA-256 to generate an order digest, constructing associated data of transaction parties, extracting the digest, inputting an elliptic curve signature to generate a transaction authorization voucher, collecting inventory change, logistics state, payment time series, constructing an e-commerce transaction state chain, encapsulating a blockchain, writing a new block record, executing a path to generate a chain transaction record voucher, calling the voucher to read the state chain, verifying the signature and data consistency, and outputting an e-commerce transaction integrity proof; in the application, identity encryption verification and data confirmation are realized by hashing and elliptic curve signature of order key data, a transaction state chain is constructed based on the signature and time series to record on a chain, inventory, payment and logistics are ensured to be consistent, on-chain vouchers support traceability verification, and the traceability, security and consistency of e-commerce transactions are improved.

Description

Technical Field

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

[0002] The blockchain technology field involves utilizing core technologies such as distributed ledgers, consensus mechanisms, cryptographic algorithms, and smart contracts to achieve secure data storage, trusted transmission, and tamper-proof management. Its technical system mainly includes block generation and verification mechanisms, node consensus protocols, on-chain data structure design, and cross-chain interaction and smart contract execution. This field is widely used in scenarios such as financial settlement, supply chain management, digital identity authentication, and the digital economy, improving the transparency and credibility of information processing through decentralization and building a trust system for multi-party collaboration.

[0003] Traditional digital economy e-commerce management methods refer to a business processing approach in an e-commerce environment that utilizes centralized databases and servers to handle commodity transactions, order management, payment settlement, and user credit assessment. This method relies on the centralized management system of the e-commerce platform for commodity information entry, inventory updates, transaction record storage, and fund flow control, and completes transaction payments and reconciliation settlements through third-party payment interfaces. During data interaction, the platform server is responsible for the unified storage and retrieval of transaction data. The generation of user credit and transaction credentials depends on internal platform rules and manual review mechanisms. Business collaboration among e-commerce participants is mainly achieved through backend system commands and interface protocols for data synchronization and management.

[0004] Current digital economy e-commerce management is centered on a centralized database. Transaction data relies on platform servers for unified storage and retrieval. Information verification and credit assessment depend on platform rules and manual review, making it difficult to independently confirm the authenticity of transaction vouchers. Data updates are subject to delays and the risk of subjective intervention. Internal platform operations cannot be externally verified, resulting in a lack of traceability throughout the transaction process. Data transmission between upstream and downstream of the supply chain relies on interface protocols, which are prone to inconsistencies due to version differences or system delays. Cross-platform collaboration makes it difficult to ensure the complete correlation of transaction data, and in the event of disputes, credible digital evidence cannot be formed, affecting the security and credibility of the e-commerce transaction system. Summary of the Invention

[0005] To address the technical problems inherent in existing digital economy e-commerce management, which relies on centralized databases, where transaction data is uniformly stored and accessed via platform servers, and where information verification and credit assessment depend on platform rules and manual review, leading to difficulties in independently confirming the authenticity of transaction vouchers, risks of data update delays and subjective interference, lack of external verification of internal platform operations resulting in a lack of traceability throughout the transaction process, reliance on interface protocols for data transmission between upstream and downstream supply chains which can easily cause inconsistencies due to version differences or system delays, difficulty in ensuring the complete correlation of transaction data during cross-platform collaboration, and the inability to form credible digital evidence to support disputes, thus affecting the security and credibility of the e-commerce transaction system, this invention provides a blockchain-based digital economy e-commerce management method. To achieve the above objectives, this invention employs a blockchain-based digital economy e-commerce management method, comprising the following steps: S1: Obtain user order data through the e-commerce platform's transaction interface, extract product identification code, transaction amount, buyer's account address, and seller's account address, concatenate the product identification code and transaction amount, and then perform SHA-256 hash function to analyze the order hash digest to construct the transaction participant association data; S2: Extract the order hash digest based on the associated data of the transaction participants, input the order hash digest into the elliptic curve digital signature algorithm for signature operation, calculate the digital signature value for the buyer's account address and the seller's account address respectively, and encapsulate it as a transaction authorization certificate; S3: Extract the digital signature value based on the transaction authorization certificate, collect the product inventory change value, logistics status identifier, and payment confirmation timestamp, and serialize and encode them with the digital signature value in chronological order to construct an e-commerce transaction status chain; S4: Based on the e-commerce transaction state chain, the state node data in the e-commerce transaction state chain is encapsulated in the blockchain transaction format, written into a new block through the blockchain consensus mechanism, the execution path of the e-commerce transaction state chain is recorded in the block data structure, and an on-chain transaction record certificate is generated.

[0006] As a further aspect of the present invention, the transaction participant association data includes an order number index, an account association mapping relationship, and a transaction fund flow identifier; the transaction authorization certificate includes buyer digital signature information, seller digital signature information, and a hash authentication digest value; the e-commerce transaction status chain includes inventory change record nodes, logistics status tracking nodes, and payment confirmation time nodes; and the on-chain transaction record certificate includes block index information, status chain path records, and timestamp identifiers.

[0007] As a further aspect of the present invention, the specific steps of S1 are as follows: S101: Obtain user order data from the e-commerce platform's transaction interface, parse the product identifier code, transaction amount, buyer's account address, and seller's account address, and concatenate the product identifier code and transaction amount into a composite string according to the order index order to generate a concatenated transaction data frame; S102: Based on the composite string data in the spliced ​​transaction data frame, perform byte encoding conversion, input the encoded byte sequence into the SHA-256 function to calculate a fixed-length hash value, perform hexadecimal transcoding, and generate an order hash digest; S103: Call the order hash digest and the buyer's account address and seller's account address in the user order data, perform index matching on the hash digest and account field, classify the matching results according to the transaction direction, and perform node index encoding processing to generate transaction participant association data.

[0008] As a further aspect of the present invention, the specific steps of S2 are as follows: S201: Based on the transaction participant association data, extract the order hash digest, read the order number, transaction amount, timestamp and account identifier fields, perform verification and byte order check on the extracted fields, and form a digest field verification set; S202: Based on the digest field verification set, the elliptic curve signature algorithm is used to extract the curve base point and private key vector, and numerical coordinate mapping and parameter association operations are performed on the digest field. The calculated coordinate values ​​are matched with random factors and the corresponding relationship is recorded to generate an intermediate dataset for signature calculation. S203: Based on the signature calculation intermediate dataset, call the buyer account address and seller account address parameters, perform hash matching and signature value calculation on the account address, calculate the account signature vector by combining the random factor, and encapsulate the signature vectors of the two accounts to generate a transaction authorization certificate.

[0009] As a further aspect of the present invention, the specific steps of S3 are as follows: S301: Obtain the transaction authorization certificate, perform field parsing on the certificate record segment and locate the signature field position, retrieve the signature index tag to read the corresponding signature data frame, perform field integrity verification and time series recording, and generate the extracted signature dataset; S302: Based on the extracted signature dataset, collect the product inventory change value, logistics status identifier and payment confirmation timestamp, perform field comparison and positional sorting according to the transaction identifier field, and perform mapping association between the formed numerical matrix and the extracted signature dataset on the index dimension to generate a transaction status parameter set; S303: Based on the timestamp sequence label of the transaction status parameter set, perform serialization encoding and sequential aggregation on the signature data field, map the logistics status identifier and inventory change value according to the index, and generate an e-commerce transaction status chain.

[0010] As a further aspect of the present invention, the specific steps of S4 are as follows: S401: Obtain the status node data in the e-commerce transaction status chain, collect the transaction event parameter set based on the transaction identifier and timestamp, and encapsulate the transaction identifier field, data hash field and signature field of the node data in a structured manner to generate a blockchain transaction encapsulation dataset; S402: Based on the blockchain transaction encapsulation dataset, call the hash field and compare it with the hash base value of the blockchain network node to determine whether the hash values ​​are equal. Classify the data frames with equal hash values ​​and generate a consensus confirmation transaction dataset. S403: Based on the consensus confirmation transaction dataset, extract the transaction index field and execution path identifier field and perform structured mapping, write the mapping result into a new block data structure, record the execution path sequence number and perform hash encapsulation, and generate on-chain transaction record certificate.

[0011] As a further aspect of the present invention, the hash base value of the blockchain network node is calculated by weighting the node key, node identifier and node timestamp, and is dynamically updated according to the time difference; The step of extracting the transaction index field and the execution path identifier field and performing structured mapping refers to arranging the execution path identifier field in ascending order according to the sequence number of the transaction index field, and encapsulating the path sequence number of the mapping result by secondary hashing with a length of 128 bits.

[0012] As a further aspect of the present invention, the method further includes step S5: S5: In response to the e-commerce platform's traceability query request, call the on-chain transaction record certificate, read the status node data in the e-commerce transaction status chain from the blockchain storage node, reverse traverse to verify the consistency of the digital signature value with the inventory change value and the logistics status identifier, and output the e-commerce transaction integrity certificate. The e-commerce transaction integrity proof includes signature consistency verification results, inventory and logistics matching verification results, and transaction credibility assessment results.

[0013] As a further aspect of the present invention, the specific steps of S5 are as follows: S501: Extract the on-chain transaction record certificate corresponding to the traceability query request of the e-commerce platform, call the e-commerce transaction status chain data of the blockchain storage node, compare the hash value of the status node with the hash value of the transaction record, remove mismatched nodes, and generate a status node sequence set. S502: Based on the state node sequence set, reverse the transaction hash values ​​of adjacent nodes, extract the digital signature value and calculate the hash verification difference, compare the verification difference with the sign bit of the inventory change record value, filter the node index with the same sign direction, aggregate the index and the signature value pair, and generate a signature consistency index set. S503: Call the signature consistency index set, retrieve the logistics status identifier field, compare the identifier at the index position with the inventory change value, calculate the matching correspondence rate, analyze the transaction status consistency judgment value based on the correspondence rate, and aggregate it with the signature verification result to obtain the e-commerce transaction integrity proof.

[0014] A blockchain-based digital economy e-commerce management system includes: The order data extraction module obtains user order data through the e-commerce platform's transaction interface, extracts product identification codes, transaction amounts, buyer account addresses, and seller account addresses, concatenates the product identification codes and transaction amounts, executes the SHA-256 hash function to analyze the order hash digest, constructs the transaction participant association data, and transmits it to the transaction signature verification module. The transaction signature verification module extracts the order hash digest based on the associated data of the transaction participants, inputs the order hash digest into the elliptic curve digital signature algorithm for signature calculation, calculates digital signature values ​​for the buyer's account address and the seller's account address respectively, encapsulates them into a transaction authorization certificate, and transmits them to the state chain construction module. The state chain construction module extracts the digital signature value based on the transaction authorization certificate, collects the product inventory change value, logistics status identifier, and payment confirmation timestamp, and serializes and encodes them with the digital signature value in chronological order to construct the e-commerce transaction state chain, which is then transmitted to the block writing module. The block writing module, based on the e-commerce transaction state chain, encapsulates the state node data in the e-commerce transaction state chain according to the blockchain transaction format, writes it into a new block through the blockchain consensus mechanism, records the execution path of the e-commerce transaction state chain in the block data structure, generates on-chain transaction record certificates, and transmits them to the traceability verification module. The traceability verification module calls the on-chain transaction record certificate in response to the traceability query request from the e-commerce platform. It reads the status node data in the e-commerce transaction status chain from the blockchain storage node, reverses the traversal to verify the consistency between the digital signature value and the inventory change value and the logistics status identifier, and outputs the e-commerce transaction integrity certificate.

[0015] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, by performing hash digest and elliptic curve digital signature operations on key order data, encrypted verification of the identities of multiple parties in the transaction and independent confirmation of data are achieved. Based on the signature results and time series, a transaction state chain is constructed and recorded on the chain, forming a verifiable time-series data structure. This ensures the consistency of inventory changes, payment confirmations, and logistics nodes. The on-chain credentials provide reversible verification evidence for multiple stages, enabling rapid verification of state integrity and signature association during traceability queries. This eliminates data trust issues caused by reliance on centralized databases and improves the traceability, security, and information consistency of e-commerce transactions throughout the entire process. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the accompanying drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the steps of the present invention; Figure 2 This is a detailed schematic diagram of S1 of the present invention; Figure 3 This is a detailed schematic diagram of S2 of the present invention; Figure 4 This is a detailed schematic diagram of S3 of the present invention; Figure 5 This is a detailed schematic diagram of S4 of the present invention; Figure 6 This is a detailed schematic diagram of S5 of the present invention; Figure 7 This is a system module diagram of the present invention. Detailed Implementation

[0018] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0019] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0020] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0021] In this embodiment of the invention, sometimes the subscript such as W1 is written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0022] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0023] Please see Figure 1 This invention provides a blockchain-based digital economy e-commerce management method, comprising the following steps: S1: Obtain user order data through the e-commerce platform's transaction interface, extract product identification code, transaction amount, buyer's account address, and seller's account address, concatenate the product identification code and transaction amount, and then perform SHA-256 hash function to analyze the order hash digest to construct the transaction participant association data; S2: Extract the order hash digest based on the transaction participant association data, input the order hash digest into the elliptic curve digital signature algorithm for signature operation, calculate the digital signature value for the buyer account address and the seller account address respectively, and encapsulate it as a transaction authorization certificate; S3: Extract digital signature values ​​based on transaction authorization certificates, collect product inventory change values, logistics status identifiers, and payment confirmation timestamps, and serialize and encode them with digital signature values ​​in chronological order to construct an e-commerce transaction status chain; S4: Based on the e-commerce transaction state chain, the state node data in the e-commerce transaction state chain is encapsulated in the blockchain transaction format, written into a new block through the blockchain consensus mechanism, the execution path of the e-commerce transaction state chain is recorded in the block data structure, and on-chain transaction record certificates are generated. S5: In response to the e-commerce platform's traceability query request, call the on-chain transaction record certificate, read the status node data in the e-commerce transaction status chain from the blockchain storage node, reverse traverse to verify the consistency of the digital signature value with the inventory change value and the logistics status identifier, and output the e-commerce transaction integrity certificate. The transaction participant association data includes order number index, account association mapping relationship and transaction fund flow identifier; the transaction authorization certificate includes buyer digital signature information, seller digital signature information and hash authentication digest value; the e-commerce transaction status chain includes inventory change record node, logistics status tracking node and payment confirmation time node; the on-chain transaction record certificate includes block index information, status chain path record and timestamp identifier; and the e-commerce transaction integrity proof includes signature consistency verification result, inventory and logistics matching verification result and transaction trustworthiness assessment result.

[0024] Please see Figure 2 The specific steps of S1 are as follows: S101: Obtain user order data from the e-commerce platform's transaction interface, parse the product identifier code, transaction amount, buyer's account address, and seller's account address, and concatenate the product identifier code and transaction amount into a composite string according to the order index order to generate a concatenated transaction data frame; Retrieve user order data in JSON format returned by the e-commerce platform's transaction interface. This data is a string of characters containing multiple key-value pairs. For example, for transaction number 202511201001, the original data would be: {"order_id":"202511201001","product_code":"SN-HW-M60P-256G","amount":8999.00,"currency":"CNY","buyer_address" ; First, the JSON character stream is parsed to locate and extract the product identifier code, specifically by searching for the key "product_code" and obtaining its corresponding value SN-HW-M60P-256G. Next, the transaction amount is located and extracted, specifically by searching for the key "amount" and obtaining its corresponding value 8999.00. Then, the buyer's account address is located and extracted, specifically by searching for the key "buyer_address" and obtaining its corresponding value 0x742d35Cc6634C0532925a3b844Bc454e4438f44e, and the seller's account address is located and extracted, specifically by searching for the key "seller_address" and obtaining its corresponding value 0. Following the preset order index order (product identifier code first, then transaction amount), the extracted product identifier code SN-HW-M60P-256G is concatenated with the transaction amount 8999.00. A fixed, unambiguous separator, such as two vertical bars ||, is inserted between the two fields during concatenation, forming a composite string SN-HW-M60P-256G||8999.00. Finally, this composite string is combined with the remaining fields extracted from the original order to form a structured data set, which is the concatenated transaction data frame. Its content is as follows: {"composite_string":"SN-HW-M60P-256G||8999.00","buyer_address":"0x742d35Cc6634C0532925a3b844Bc454e4438f44e","seller_address":"0xAb5801a7D398351b8bE11C439e05C5B3259aeC9B"}, this is the generated spliced ​​transaction data frame.

[0025] S102: Based on the composite string data in the concatenated transaction data frame, perform byte encoding conversion, input the encoded byte sequence into the SHA-256 function to calculate a fixed-length hash value, perform hexadecimal transcoding, and generate an order hash digest; Based on the generated concatenated transaction data frame, the composite string data, SN-HW-M60P-256G||8999.00, is retrieved. Byte encoding conversion is performed on this string, specifically converting it into a byte sequence according to the UTF-8 encoding standard. This conversion process maps each character, including letters, numbers, hyphens, and vertical bars, to its corresponding byte representation. The resulting complete byte sequence is then used as input data to the SHA-256 hash function for calculation. The SHA-256 function's execution includes preprocessing the input byte sequence by adding padding bits and length information to ensure its total length is a multiple of 512 bits. The processed data block is then internally encrypted and compressed through 64 rounds of cyclic encryption. Each round involves complex bit operations, such as bit shifting, XOR, NAND, and AND operations. The hash is calculated using a fixed set of hash constants, ultimately generating a 256-bit binary value. This 256-bit binary value is the fixed-length hash value. Since binary form is inconvenient for display and transmission, it needs to be converted to hexadecimal. This process involves converting the 256-bit binary sequence from high to low bits, grouping every 4 bits into a corresponding hexadecimal character (0-9, af). For example, binary 1010 is converted to hexadecimal 'a', and 1111 is converted to 'f'. After 64 such conversions, a string of 64 hexadecimal characters is finally obtained. For the input compound string SN-HW-M60P-256G||8999.00, the calculated hexadecimal string is 8a5b6c7d... (this is an example hash value). This 64-bit string is the unique order hash digest for this order.

[0026] S103: Call the order hash digest and the buyer's account address and seller's account address in the user order data, perform index matching on the hash digest and account field, classify the matching results by transaction direction, and perform node index encoding processing to generate transaction participant association data; The generated order hash digest 8a5b6c7d... is called, and combined with the buyer account address 0x742d35Cc6634C0532925a3b844Bc454e4438f44e and the seller account address 0xAb5801a7D398351b8bE11C439e05C5B3259aeC9B from the obtained user order data, these three fields are indexed and matched. Specifically, a new data record is created, and the order hash digest is... Use 8a5b6c7d... as the primary key or unique index for this record, and store the buyer's and seller's account addresses as attribute values ​​for this record. Then, categorize the matching results according to the flow of transaction funds. For example, categorize the buyer's account address (0x742d35Cc6634C0532925a3b844Bc454e4438f44e) into the funder's address field, and categorize the seller's account address (0xAb5801a7D398351b8bE11C439e0) into the funder's address field. 5C5B3259aeC9B is categorized under the payee address field. Next, node index encoding processing is performed. This process requires maintaining a global "node address and index encoding lookup table," which records the unique account addresses and their corresponding integer indices. When processing this transaction, the system first checks if the buyer's account address 0x742d35Cc6634C0532925a3b844Bc454e4438f44e already exists in the table. If it does, it is directly retrieved. If the corresponding index code, such as 1024, does not exist, a new record is added to the table, the address is stored, and a new, unique, sequentially increasing integer is assigned as its index code. For example, if the current maximum index is 2047, the newly assigned index is 2048. The same query and allocation operation is performed on the seller account address 0xAb5801a7D398351b8bE11C439e05C5B3259aeC9B to obtain its index code, such as 1536.

[0027] Table 1: Node Address and Index Encoding Correspondence Table As shown in Table 1, this table maintains the mapping relationship between the account addresses of participants in the blockchain network and their simplified digital identifiers within the system. Finally, the order hash digest, the categorized addresses of the funders and payees, and the corresponding node index codes are combined to generate structured transaction participant association data, the specific content of which is as follows: {"order_hash":"8a5b6c7d...","payer_address":"0x742d35Cc6634C0532925a3b844Bc454e4438f44e","payee_add ress":"0xAb5801a7D398351b8bE11C439e05C5B3259aeC9B","payer_node_index":1024,"payee_node_index":1536}.

[0028] Please see Figure 3 The specific steps of S2 are as follows: S201: Based on the transaction participant association data, extract the order hash digest, read the order number, transaction amount, timestamp and account identifier fields, perform validation and byte order verification on the extracted fields, and form a digest field validation set; Based on the generated transaction participant association data, namely: {"order_hash":"8a5b6c7d...","payer_address":"0x742d...","payee_address":"0xAb58...","payer_node_index":1024,"payee_node_index":1536}; First, the order hash digest 8a5b6c7d... is extracted. Then, the system uses this hash digest or the associated order ID 202511201001 as the query key to read the associated core transaction fields from the e-commerce platform's original order database. This includes the order number 202511201001, the transaction amount 8999.00, the Unix timestamp 1732068661 indicating the transaction occurred, and the account identifier field, i.e., the buyer's account address. The string 0x742d35Cc6634C0532925a3b844Bc454e4438f44e is compared to the seller account address 0xAb5801a7D398351b8bE11C439e05C5B3259aeC9B. Next, each extracted field is validated. For the order hash digest 8a5b6c7d..., it is checked whether its string length is 64 characters, and whether all characters are hexadecimal numbers between 0-9 and 'af'. Within the specified range, for the transaction amount 8999.00, it is determined whether its value is greater than 0. For the timestamp 1732068661, it is determined whether it is less than the current system time and not earlier than a preset system startup timestamp. For the buyer's and seller's account addresses, it is determined whether their format starts with 0x, whether the length is 42 characters, and whether the following 40 characters are all hexadecimal characters. After the field format validation passes, a byte order check is performed, converting the numeric transaction amount 8999.00 and timestamp 1732068661 into a fixed-length byte sequence, such as 8 bytes of unsigned long long, and specifying that the conversion uses big-endian byte order, that is, the most significant byte first and the least significant byte last, forming a unified byte representation standard. Finally, the validated order hash digest, the formatted account address, and the byte order standardized amount and timestamp byte sequence are integrated together to form a digest field validation set.

[0029] S202: Based on the digest field verification set, the elliptic curve signature algorithm is used to extract the curve base point and private key vector, and numerical coordinate mapping and parameter association operations are performed on the digest field. The calculated coordinate values ​​are matched with random factors and the corresponding relationship is recorded to generate an intermediate dataset for signature calculation. Based on the formed digest field verification set, which contains the core data to be signed, namely the hash value calculated by combining the order fields, we continue to use the order hash digest 8a5b6c7d... as the message to be signed. First, for the buyer performing the signing, the parameters of the elliptic curve secp256k1 are extracted from their encrypted wallet or security module. The fixed curve base point G is extracted, which is a publicly known point on the curve with known coordinates. And the parameters related to the buyer's account address are extracted. 0x742d35Cc6634C0532925a3b844Bc454e4438f44e; The uniquely corresponding private key vector d is a 256-bit secret integer, for example: E9873D79C6D87DC0FB6A5778633389F4453213303DA61F20BD67FC233AA33262; Next, a numerical coordinate mapping is performed on the digest field, converting the hexadecimal order hash digest 8a5b6c7d... into a large integer h. Then, a parameter association operation is performed. This operation begins by generating a 256-bit random integer used only once as a random factor k, for example, A5025F7E870A34907329584364491295D2989A517593280B35A221E24933C648. Subsequently, a scalar multiplication operation on the elliptic curve is performed, i.e., calculating point P = k × G to obtain a new point P. The x-coordinate value of this point P is taken and modulo the order n of the curve to obtain a part of the signature r. Then, the multiplicative inverse k of order n is calculated. -1 Then calculate the expression (h+r×d)(modn), and compare this result with k. -1 Multiply the results and take the modulo of n again to obtain the other part of the signature, s. Record the correspondence between the calculated r value and the random factor k instantaneously. Combine the r value and the s value to be calculated, along with the original hash h and the private key d, to form the intermediate dataset for signature calculation.

[0030] S203: Based on the signature calculation intermediate dataset, call the buyer's account address and seller's account address parameters, perform hash matching and signature value calculation on the account address, combine random factors to calculate the account signature vector, and encapsulate the two account signature vectors to generate a transaction authorization certificate; Calculate the intermediate dataset based on the generated signature, which contains the r value needed to calculate the signature and other related parameters, and then call the buyer's account address: 0x742d35Cc6634C0532925a3b844Bc454e4438f44e; With seller account address: 0xAb5801a7D398351b8bE11C439e05C5B3259aeC9B; Perform a hash match on the account address; this process verifies the private key d that will be used for signing. buyerAfter the corresponding public key is hashed and formatted, it is checked whether it can generate an address string that is completely identical to the buyer's account address 0x742d35Cc6634C0532925a3b844Bc454e4438f44e. This confirms the ownership of the private key. If the match is successful, the signature value s is completed. buyer The calculation yields the buyer's signature vector, which is composed of the r value and s. buyer A pair of values ​​(r, s) buyer Subsequently, the system notifies the seller to perform the same signature process on the hash digest 8a5b6c7d... of the same order. The seller system extracts the signature from its security module, which is related to the seller's account address. 0xAb5801a7D398351b8bE11C439e05C5B3259aeC9B; The corresponding private key d seller And generate a new random factor k belonging to the seller. seller Using the same elliptic curve calculation steps described above, the seller's signature vector (r) is calculated. seller s seller Next, the signature vectors of the two accounts are encoded and encapsulated separately, and the buyer's numerical pair (r, s) is encapsulated. buyer ) and seller's numerical pair (r seller s seller The signatures are encoded according to the DER (Distinguished Encoding Rules) standard and converted into a byte sequence that can be transmitted and stored. Finally, the two encoded signature sequences, together with the order hash digest and the account addresses of both parties, are encapsulated into a structured data packet, which is the transaction authorization certificate.

[0031] Please see Figure 4 The specific steps of S3 are as follows: S301: Obtain the transaction authorization certificate, perform field parsing on the certificate record segment and locate the signature field position, retrieve the signature index tag to read the corresponding signature data frame, perform field integrity verification and time series recording, and generate the extracted signature dataset; Retrieve the generated transaction authorization certificate data packet. This data packet is structured data containing {"order_hash":"8a5b6c7d...","payer_address":"0x742d...","payee_address":"0xAb58...","payer_signature":"DER_encoded_bytes_for_buyer","payee_signature":"DER_encoded_bytes_for_seller"}. Perform field parsing on this certificate record segment, i.e., traverse the key-value pairs in the data packet. First, locate payer_signature as the first signature index tag, and read its corresponding DER_encoded_bytes_for_buyer as the buyer's signature data frame. Then, locate payee_signature as the second signature index tag, and read its corresponding DER_encoded_bytes_for_seller as the seller's signature data frame. Next, perform field integrity checks, checking if the order_hash field exists and has a length of 64, and if the payer_address field exists and has a length of 42. The process checks if the `payee_address` field exists and is 42 characters long, and if both `payer_signature` and `payee_signature` fields are not empty. If either check is negative, the voucher is marked as invalid. If both checks are positive, execution continues, and time-series recording is performed. This involves calling the system's current time function to obtain a high-precision Unix timestamp, such as 1732069261, and associating this timestamp with the extracted buyer and seller signature data frames. Finally, the verified order hash digest, buyer signature data frame, seller signature data frame, and recorded receive timestamp group are combined. A new structured data set is synthesized, containing the following content: {"order_hash":"8a5b6c7d...","buyer_signature_frame":"DER_encoded_bytes_for_buyer","seller_signature_frame":"DER_encoded_bytes_for_seller","reception_timestamp":1732069261,"integrity_status":"OK"}. This is the generated signature extraction dataset.

[0032] S302: Based on the extracted signature dataset, collect the product inventory change value, logistics status identifier and payment confirmation timestamp, perform field comparison and position sorting according to the transaction identifier field, and perform mapping association with the extracted signature dataset on the index dimension to generate the transaction status parameter set; Based on the generated signature extraction dataset, {"order_hash":"8a5b6c7d...","buyer_signature_frame":"...","seller_signature_frame":"...","reception_timestamp":1732069261,"integrity_status":"OK"}, real-time status information associated with the transaction is collected through an external interface. First, a query is initiated to the warehouse management system (WMS) API using the product identifier code SN-HW-M60P-256G from the original order to obtain the product's outbound record, resulting in a product inventory change value of -1. Next, a query is initiated to the logistics information system API using order number 202511201001 to obtain the current package's logistics status identifier. This identifier is a predefined integer code, for example, 10 represents "packed and awaiting pickup," and 20 represents "picked up and in transit." Here, the collected status is 10. Next, a query is initiated to the payment gateway's API using the order number or payment transaction number to obtain the precise timestamp confirming successful payment from the payment system. The collected payment confirmation timestamp is 1732069000. After collection, based on the transaction identifier field, i.e., the order hash 8a5b6c7d..., a field comparison is performed. The inventory change returned by the WMS, the status identifier returned by the logistics system, and the timestamp returned by the payment gateway are matched with the order hash in the currently processed signature extraction dataset to confirm that the collected data all correspond to the same transaction. Subsequently, positional sorting is performed, arranging the data from different sources in a fixed order of [payment confirmation timestamp, product inventory change value, logistics status identifier] to form a numerical vector [1732069000, -1, 10]. This is a single-row instance of the numerical matrix. Finally, this formed numerical matrix is ​​mapped and associated with the signature extraction dataset on the index dimension, that is, the order hash 8a5b6c7d... is used as the unique key to combine the signature extraction dataset and this numerical vector into a more complete data structure, generating a transaction status parameter set.

[0033] S303: Based on the timestamp sequence label of the transaction status parameter set, perform serialization encoding and sequential aggregation on the signature data field, map the logistics status identifier and inventory change value according to the index, and generate an e-commerce transaction status chain; Based on the generated transaction status parameter set, whose data structure is {"order_hash":"8a5b6c7d...","signatures":{...},"reception_timestamp":1732069261,"payment_timestamp":1732069000,"stock_change":-1,"logistics_status":10}, firstly, referring to the timestamp order label within this set, i.e., the value of payment_timestamp 1732069000 is earlier than the value of reception_timestamp 1732069261, the event order of "payment confirmation" preceding "document receipt" is determined. Subsequently, serialization encoding is performed on the signature data field, that is... The buyer's signature data frame and the seller's signature data frame in the signatures object are concatenated in a fixed buyer-seller order to form a longer byte sequence, which is then sequentially aggregated. This aggregated signature sequence is combined with the remaining status data in the order of [payment timestamp, inventory change, logistics status, aggregated signature sequence]. Next, the logistics status identifier 10 and the inventory change value -1 are mapped according to the order hash 8a5b6c7d... index, that is, the status value is explicitly bound to the current status record of the transaction. Finally, this record that aggregates the current status information is used as a new status node, a SHA-256 hash value is calculated for this node as its node hash, and the hash value pointing to the previous status node associated with this order is recorded (if it is the first node, this value is null), thus linking the new node to the existing chain.

[0034] Table 2: E-commerce Transaction State Chain (Partial Examples) As shown in Table 2, the table shows how the different state nodes for the same e-commerce transaction 202511201001 are linked in chronological order. The 9d8c... node is the latest node generated in this operation, which includes the payment, authorization, logistics and inventory status. The generation of this node marks the recording of a new and verifiable transaction status, which constitutes part of the e-commerce transaction status chain.

[0035] Please see Figure 5 The specific steps of S4 are as follows: S401: Obtain state node data in the e-commerce transaction state chain, collect transaction event parameter sets based on transaction identifiers and timestamps, and encapsulate the transaction identifier field, data hash field, and signature field of the node data in a structured manner to generate a blockchain transaction encapsulation dataset; The latest state node data in the generated e-commerce transaction state chain is obtained, specifically the data record with node hash 9d8c... in Table 2. Based on the transaction identifier 8a5b6c7d... and record timestamp 1732069261 of this node, the transaction event parameter set encapsulated within this node is collected. This parameter set includes payment confirmation timestamp 1732069000, inventory change value -1, logistics status identifier 10, and aggregated buyer and seller signature data. Next, the core fields extracted from the state node are structured and encapsulated. Specifically, a new data structure is created, which is prepared to be submitted to the blockchain network and contains a structure named "transaction". The `_id` field is set to the transaction identifier of the state node, i.e., the order hash 8a5b6c7d...; the `state_data_hash` field is set to the hash value of the node in the e-commerce transaction state chain 9d8c...; the `signature_payload` field is set to the byte sequence of signature data from the buyer and seller extracted from the state node, encoded by DER, and concatenated; in addition, there is a composite field `related_state_data`, which stores parameters such as inventory change -1 and logistics status 10. This newly constructed data structure is the blockchain transaction encapsulation dataset.

[0036] S402: Based on the blockchain transaction encapsulation dataset, call the hash field and compare it with the hash benchmark value of the blockchain network node to determine whether the hash values ​​are equal. Classify the data frames with equal hash values ​​and generate a consensus confirmation transaction dataset. Based on the generated blockchain transaction encapsulation dataset, namely {"transaction_id":"8a5b6c7d...", "state_data_hash":"9d8c...", ...}, the consensus node first calls the hash field `state_data_hash`, whose value is 9d8c..., and compares it with the hash base value recalculated by the node based on the corresponding state node data. The hash base value of the blockchain network node is recalculated by the blockchain network node based on the state node data corresponding to the blockchain transaction encapsulation dataset. Specifically, the blockchain network node, based on the `transaction_id` field in the blockchain transaction encapsulation dataset, calls the state node data in the e-commerce transaction state chain corresponding to that `transaction_id`, reads the transaction identifier, payment confirmation timestamp, inventory change value, logistics status identifier, and the hash value of the previous node from that state node, and serializes it according to the field structure when the state node was formed. The serialized state node data is then input into the SHA-256 hash function for calculation to obtain the recalculated state node hash value on the node side. Since the data source used in this recalculation process is the same as the data source when the state node was formed, the recalculated state node hash value on the node side should match the state_data_hash field in the blockchain transaction encapsulation dataset, provided the state node data has not been tampered with. Next, the system performs a judgment operation, comparing the hash value 9d8c... extracted from the dataset with the recalculated state node hash value on the node side using a string-complete match. If they match completely, the transaction_id of the data frame, i.e., 8a5b6c7d..., is added to a temporary set. This set stores the data frame indices that passed the hash comparison in this round of consensus, thereby generating the consensus confirmation transaction dataset.

[0037] S403: Based on the consensus-confirmed transaction dataset, extract the transaction index field and execution path identifier field and perform structured mapping. Write the mapping result into the new block data structure, record the execution path sequence number and perform hash encapsulation to generate on-chain transaction record credentials. Based on the generated consensus-confirmed transaction dataset, which is a list containing multiple transaction IDs that have passed consensus (e.g., ["8a5b6c7d...", "a1b2c3d4...", "f9e8d7c6..."), the system first extracts the corresponding transaction index field and execution path identifier field for each transaction ID in the list. The transaction index field is the transaction ID itself, while the execution path identifier field is a code assigned according to the business type when the transaction is created. For example, 8a5b6c7d... corresponds to STANDARD_PURCHASE_V1, a1b2c3d4... corresponds to REFUND_REQUEST_V2, and f9e8d7c6... also corresponds to STANDARD_PURCHASE_V1. Next, structured mapping is performed. This process refers to arranging the corresponding execution path identifier fields according to the order in which the transaction index fields appear in the consensus-confirmed transaction dataset, i.e., ["8a5b6c7d...", "a1b2c3d4...", "f9e8d7c6..."], forming a path sequence. ["STANDARD_PURCHASE_V1","REFUND_REQUEST_V2","STANDARD_PURCHASE_V1"]; Then, the path sequence of this mapping result is encapsulated using a secondary hash. Specifically, the strings in the path sequence are first concatenated using the delimiter "-" to form a long string: STANDARD_PURCHASE_V1-REFUND_REQUEST_V2-STANDARD_PURCHASE_V1. This long string is then hashed using the MD5 function, which outputs a 128-bit hash value, for example, 1a2b3c4d5e6f7a8b9c0d1e2f3a4b5c6d. The 128-bit hash value is the hash encapsulation result of the path sequence number. Finally, the complete data structure of the transactions in the consensus confirmation transaction dataset is written into the "Body" part of a new block, and the calculated 128-bit path sequence hash 1a2b3c4d5e6f7a8b9c0d1e2f3a4b5c6d is written into a specific field execution_path_root in the "Block Header" of the new block. After the block is packaged, an immutable on-chain transaction record certificate is generated.

[0038] Please see Figure 6 The specific steps of S5 are as follows: S501: Extract the on-chain transaction record voucher corresponding to the traceability query request of the e-commerce platform, call the e-commerce transaction status chain data of the blockchain storage node, compare the hash value of the status node with the hash value of the transaction record, remove mismatched nodes, and generate a status node sequence set. The system extracts the on-chain transaction record credential specified in the traceability query request for order number 202511201001, specifically locating the block containing transaction_id 8a5b6c7d... and retrieving its corresponding record data from the transaction body of that block. This record contains a state_data_hash field with a value of 9d8c.... Next, it calls the blockchain storage node storing the detailed history of this transaction to retrieve the e-commerce transaction state chain data associated with transaction_id 8a5b6c7d... This data is a series of state nodes arranged chronologically, as shown in Table 2, including the order creation node with hash 5f2b... and the two-party authorization node with hash 9d8c... Subsequently, the hash value of the state node is compared with the transaction record hash value 9d8c... extracted from the on-chain transaction record credential. Specifically, the system first verifies the internal integrity of the state chain, starting from the latest node... Starting with 9d8c..., the process checks if the hash field of its predecessor node is 5f2b..., then finds the node with the hash 5f2b... and confirms its existence. This process is recursively repeated until the genesis node. After confirming that the internal links of the chain are correct, the final state hash 9d8c... of the on-chain credential record is matched precisely with the hash of the latest node in the state chain to determine if they are completely equal. If they are not equal, the entire state chain is considered invalid. At the same time, if any node's predecessor hash pointer is broken, or if a node's actual hash value does not match the hash value recalculated from its content, the node is defined as a mismatched node and removed from the verification sequence. In this example, the internal links are all correct, and the final node hashes match, so no node is removed. Finally, the nodes that have been compared and verified, i.e., the two nodes with hashes 5f2b... and 9d8c..., are reorganized according to their original chronological order in the state chain to generate a state node sequence set.

[0039] S502: Based on the state node sequence set, reverse the transaction hash values ​​of adjacent nodes, extract the digital signature value and calculate the hash verification difference, compare the verification difference with the sign bit of the inventory change record value, filter the node index with the same sign direction, aggregate the index and the signature value pair, and generate a signature consistency index set. Based on the generated set of state node sequences, i.e., an ordered list containing [Node(5f2b...), Node(9d8c...)], the system begins to traverse the sequence in reverse, starting from the latest node Node(9d8c...), extracting the encapsulated digital signature values, i.e., buyer_signature_frame and seller_signature_frame, and calculating the hash verification difference. This calculation process is as follows: First, for the buyer's signature, the system extracts its signature value (r, s...). buyer The system extracts the signed data from the previous node (5f2b...), namely the hash digest of the original order (8a5b6c7d...). Simultaneously, it derives the buyer's public key from the buyer's account address (0x742d...), and then performs the standard elliptic curve signature verification operation. If the verification passes, the hash check difference is set to 0; if it fails, it is set to 1. In this example, the verification passes, so the hash check difference is 0. Next, this hash check difference of 0 is compared with the sign bit of the inventory change record value -1 in the current node (9d8c...). The sign bit of the inventory change value -1 is negative. According to the system's default rules, a successful signature verification (check difference of 0) is considered to be related to a reduction in assets or inventory. Authorization actions with a negative sign are considered to be consistent in direction, while failed verifications (with a verification difference of 1) are considered to be inconsistent in direction. Here, the success direction represented by a verification difference of 0 is consistent with the negative sign direction of the inventory change value. Therefore, the system selects the index 9d8c... of the current node and the corresponding buyer signature to form a key-value pair {"index":"9d8c...","signature":"DER_encoded_bytes_for_buyer"}. The same verification and comparison process is performed on the seller's signature, which also yields a consistent result in direction and forms a corresponding key-value pair. Finally, the node indexes with consistent sign direction and the signature value pairs are aggregated to generate a signature consistency index set.

[0040] S503: Call the signature consistency index set, retrieve the logistics status identifier field, compare the identifier at the index position with the inventory change value, calculate the matching rate, analyze the transaction status consistency judgment value based on the matching rate, and aggregate it with the signature verification result to obtain the e-commerce transaction integrity proof. The generated signature consistency index set is invoked. This set contains [{"index":"9d8c...","signature":"buyer_sig"},{"index":"9d8c...","signature":"seller_sig"}]. The system uses the index 9d8c... to retrieve the corresponding node data in the status node sequence set and locates the logistics status identifier field, which has a value of 10. Then, the logistics status identifier 10 (packed and awaiting pickup) at the index position 9d8c... is compared with the inventory change value -1 within the same node. This comparison is a logical consistency judgment. According to the preset business rules, as shown in Table 3, when the inventory change is negative, the valid initial logistics status should be in the range of 10 to 30. The current status 10 meets this rule, so it is judged as a match. Next, the matching correspondence rate is calculated. The calculation method for this rate is: the total number of nodes with inventory changes in the entire status node sequence set is used as the denominator, and the number of nodes whose inventory changes and logistics status logically match is used as the numerator. The two are divided to obtain the result. In this simple scenario, only Node (9d8c...) experienced an inventory change, and the logic matched. Therefore, the number of matched nodes is 1, the total number of nodes is 1, and the matching rate is 1.0. Then, based on this matching rate, the transaction status consistency judgment value is analyzed. The system sets a benchmark value for the matching rate, which is set with reference to the average logistics-inventory data collaboration accuracy rate of the e-commerce platform, for example, 0.95. By comparing the calculated matching rate of 1.0 with the benchmark value of 0.95, since 1.0 is greater than 0.95, the transaction status consistency judgment value is "highly consistent". Finally, this judgment value "highly consistent" is aggregated with the obtained signature verification result (i.e., all signatures are verified successfully) to form a structured JSON object {"signature_verification_status":"OK", "state_consistency_verdict":"highly consistent", "final_proof_status":"Verified"}, thus obtaining the final proof of e-commerce transaction integrity.

[0041] Table 3: Logical Matching Rules for Inventory and Logistics Status As shown in Table 3, this table defines the logical correspondence between inventory changes and logistics status codes, providing a quantitative basis for determining the consistency of transaction status.

[0042] Please see Figure 7 A blockchain-based digital economy e-commerce management system, including: The order data extraction module obtains user order data through the e-commerce platform's transaction interface, extracts product identification codes, transaction amounts, buyer account addresses, and seller account addresses, concatenates the product identification codes and transaction amounts, executes the SHA-256 hash function to analyze the order hash digest, constructs the transaction participant association data, and transmits it to the transaction signature verification module. The transaction signature verification module extracts the order hash digest based on the associated data of the transaction participants, inputs the order hash digest into the elliptic curve digital signature algorithm for signature calculation, calculates digital signature values ​​for the buyer's account address and the seller's account address respectively, encapsulates them into a transaction authorization certificate, and passes them to the state chain construction module. The state chain construction module extracts the digital signature value based on the transaction authorization certificate, collects the product inventory change value, logistics status identifier, and payment confirmation timestamp, and serializes and encodes them with the digital signature value in chronological order to construct the e-commerce transaction state chain, which is then transmitted to the block writing module. The block writing module, based on the e-commerce transaction state chain, encapsulates the state node data in the e-commerce transaction state chain according to the blockchain transaction format, writes it into a new block through the blockchain consensus mechanism, records the execution path of the e-commerce transaction state chain in the block data structure, generates on-chain transaction record certificates, and transmits them to the traceability and verification module. The traceability verification module calls on-chain transaction record credentials for traceability query requests from e-commerce platforms, reads status node data in the e-commerce transaction status chain from blockchain storage nodes, reverses the traversal to verify the consistency between digital signature values, inventory change values, and logistics status identifiers, and outputs proof of e-commerce transaction integrity.

[0043] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A blockchain-based digital economy e-commerce management method, characterized in that, Includes the following steps: S1: Obtain user order data through the e-commerce platform's transaction interface, extract product identification code, transaction amount, buyer's account address, and seller's account address, concatenate the product identification code and transaction amount, and then perform SHA-256 hash function to analyze the order hash digest to construct the transaction participant association data; S2: Extract the order hash digest based on the associated data of the transaction participants, input the order hash digest into the elliptic curve digital signature algorithm for signature operation, calculate the digital signature value for the buyer's account address and the seller's account address respectively, and encapsulate it as a transaction authorization certificate; S3: Extract the digital signature value based on the transaction authorization certificate, collect the product inventory change value, logistics status identifier, and payment confirmation timestamp, and serialize and encode them with the digital signature value in chronological order to construct an e-commerce transaction status chain; S4: Based on the e-commerce transaction state chain, the state node data in the e-commerce transaction state chain is encapsulated in the blockchain transaction format, written into a new block through the blockchain consensus mechanism, the execution path of the e-commerce transaction state chain is recorded in the block data structure, and an on-chain transaction record certificate is generated.

2. The blockchain-based digital economy e-commerce management method according to claim 1, characterized in that, The transaction participant association data includes order number index, account association mapping relationship and transaction fund flow identifier; the transaction authorization certificate includes buyer digital signature information, seller digital signature information and hash authentication digest value; the e-commerce transaction status chain includes inventory change record node, logistics status tracking node and payment confirmation time node; and the on-chain transaction record certificate includes block index information, status chain path record and timestamp identifier.

3. The blockchain-based digital economy e-commerce management method according to claim 1, characterized in that, The specific steps of S1 are as follows: S101: Obtain user order data from the e-commerce platform's transaction interface, parse the product identifier code, transaction amount, buyer's account address, and seller's account address, and concatenate the product identifier code and transaction amount into a composite string according to the order index order to generate a concatenated transaction data frame; S102: Based on the composite string data in the spliced ​​transaction data frame, perform byte encoding conversion, input the encoded byte sequence into the SHA-256 function to calculate a fixed-length hash value, perform hexadecimal transcoding, and generate an order hash digest; S103: Call the order hash digest and the buyer's account address and seller's account address in the user order data, perform index matching on the hash digest and account field, classify the matching results according to the transaction direction, and perform node index encoding processing to generate transaction participant association data.

4. The blockchain-based digital economy e-commerce management method according to claim 3, characterized in that, The specific steps of S2 are as follows: S201: Based on the transaction participant association data, extract the order hash digest, read the order number, transaction amount, timestamp and account identifier fields, perform verification and byte order check on the extracted fields, and form a digest field verification set; S202: Based on the digest field verification set, the elliptic curve signature algorithm is used to extract the curve base point and private key vector, and numerical coordinate mapping and parameter association operations are performed on the digest field. The calculated coordinate values ​​are matched with random factors and the corresponding relationship is recorded to generate an intermediate dataset for signature calculation. S203: Based on the signature calculation intermediate dataset, call the buyer account address and seller account address parameters, perform hash matching and signature value calculation on the account address, calculate the account signature vector by combining the random factor, and encapsulate the signature vectors of the two accounts to generate a transaction authorization certificate.

5. The blockchain-based digital economy e-commerce management method according to claim 4, characterized in that, The specific steps for S3 are as follows: S301: Obtain the transaction authorization certificate, perform field parsing on the certificate record segment and locate the signature field position, retrieve the signature index tag to read the corresponding signature data frame, perform field integrity verification and time series recording, and generate the extracted signature dataset; S302: Based on the extracted signature dataset, collect the product inventory change value, logistics status identifier and payment confirmation timestamp, perform field comparison and positional sorting according to the transaction identifier field, and perform mapping association between the formed numerical matrix and the extracted signature dataset on the index dimension to generate a transaction status parameter set; S303: Based on the timestamp sequence label of the transaction status parameter set, perform serialization encoding and sequential aggregation on the signature data field, map the logistics status identifier and inventory change value according to the index, and generate an e-commerce transaction status chain.

6. The blockchain-based digital economy e-commerce management method according to claim 5, characterized in that, The specific steps of S4 are as follows: S401: Obtain the status node data in the e-commerce transaction status chain, collect the transaction event parameter set based on the transaction identifier and timestamp, and encapsulate the transaction identifier field, data hash field and signature field of the node data in a structured manner to generate a blockchain transaction encapsulation dataset containing the transaction identifier field, data hash field and signature field. S402: Based on the blockchain transaction encapsulation dataset, the blockchain network node reads the transaction identifier field, data hash field, and signature field, determines the corresponding state node based on the transaction identifier field, performs a consistency comparison between the data hash field and the node hash value of the corresponding state node, categorizes the data frames that pass the consistency comparison, and generates a consensus confirmation transaction dataset. S403: Based on the consensus confirmation transaction dataset, extract the transaction index field and execution path identifier field and perform structured mapping, write the mapping result into a new block data structure, record the execution path sequence number and perform hash encapsulation, and generate on-chain transaction record certificate.

7. The blockchain-based digital economy e-commerce management method according to claim 6, characterized in that, The hash base value of the blockchain network node is the hash value obtained by the blockchain network node re-performing hash calculation based on the state node data corresponding to the blockchain transaction encapsulation dataset, according to the field structure when the state node was formed. The step of extracting the transaction index field and the execution path identifier field and performing structured mapping refers to arranging the execution path identifier field in ascending order according to the sequence number of the transaction index field, and encapsulating the path sequence number of the mapping result by secondary hashing with a length of 128 bits.

8. The blockchain-based digital economy e-commerce management method according to claim 1, characterized in that, The method also includes step S5: S5: In response to the e-commerce platform's traceability query request, call the on-chain transaction record certificate, read the status node data in the e-commerce transaction status chain from the blockchain storage node, reverse traverse to verify the consistency of the digital signature value with the inventory change value and the logistics status identifier, and output the e-commerce transaction integrity certificate. The e-commerce transaction integrity proof includes signature consistency verification results, inventory and logistics matching verification results, and transaction credibility assessment results.

9. The blockchain-based digital economy e-commerce management method according to claim 8, characterized in that, The specific steps of S5 are as follows: S501: Extract the on-chain transaction record certificate corresponding to the traceability query request of the e-commerce platform, call the e-commerce transaction status chain data of the blockchain storage node, compare the hash value of the status node with the hash value of the transaction record, remove mismatched nodes, and generate a status node sequence set. S502: Based on the state node sequence set, reverse the transaction hash values ​​of adjacent nodes, extract the digital signature value and calculate the hash verification difference, compare the verification difference with the sign bit of the inventory change record value, filter the node index with the same sign direction, aggregate the index and the signature value pair, and generate a signature consistency index set. S503: Call the signature consistency index set, retrieve the logistics status identifier field, compare the identifier at the index position with the inventory change value, calculate the matching correspondence rate, analyze the transaction status consistency judgment value based on the correspondence rate, and aggregate it with the signature verification result to obtain the e-commerce transaction integrity proof.

10. A blockchain-based digital economy e-commerce management system, characterized in that: The system is used to implement the blockchain-based digital economy e-commerce management method according to any one of claims 1-9, and the system includes: The order data extraction module obtains user order data through the e-commerce platform's transaction interface, extracts product identification codes, transaction amounts, buyer account addresses, and seller account addresses, concatenates the product identification codes and transaction amounts, executes the SHA-256 hash function to analyze the order hash digest, constructs the transaction participant association data, and transmits it to the transaction signature verification module. The transaction signature verification module extracts the order hash digest based on the associated data of the transaction participants, inputs the order hash digest into the elliptic curve digital signature algorithm for signature calculation, calculates digital signature values ​​for the buyer's account address and the seller's account address respectively, encapsulates them into a transaction authorization certificate, and transmits them to the state chain construction module. The state chain construction module extracts the digital signature value based on the transaction authorization certificate, collects the product inventory change value, logistics status identifier, and payment confirmation timestamp, and serializes and encodes them with the digital signature value in chronological order to construct the e-commerce transaction state chain, which is then transmitted to the block writing module. The block writing module, based on the e-commerce transaction state chain, encapsulates the state node data in the e-commerce transaction state chain according to the blockchain transaction format, writes it into a new block through the blockchain consensus mechanism, records the execution path of the e-commerce transaction state chain in the block data structure, generates on-chain transaction record certificates, and transmits them to the traceability verification module. The traceability verification module calls the on-chain transaction record certificate in response to the traceability query request from the e-commerce platform. It reads the status node data in the e-commerce transaction status chain from the blockchain storage node, reverses the traversal to verify the consistency between the digital signature value and the inventory change value and the logistics status identifier, and outputs the e-commerce transaction integrity certificate.

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