A blockchain-based logistics packaging traceability data transmission system and method

Abstract

The application discloses a logistics package packaging traceability data transmission system and method based on a block chain, relates to the field of computer information technology, and aims to solve the problem that a traditional traceability mechanism cannot effectively monitor the physical state of packaging and trace tampering behavior in the transportation process, resulting in the problem that data is credible but the physical object is suspicious. The original surface information of logistics packaging is collected, a filter bank is used to obtain a filtering response matrix of a height field matrix, each filtering response matrix is converted into a binary sequence string and spliced into a binary feature code, the binary feature code is used to form a feature code sequence by extracting an invariable bit, an original fingerprint is obtained through hash calculation, a data body containing an identity code, the original fingerprint, error correction auxiliary data and a time stamp is constructed, and the data body is broadcast to a block chain after being signed by an elliptic curve digital signature; current surface features are obtained and processed to obtain a current feature code sequence; and the packaging integrity is determined by comparing the current feature code sequence with the original fingerprint.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of computer information technology, and in particular to a logistics packaging traceability data transmission system and method based on a blockchain. BACKGROUND

[0002] In the modern commodity circulation system, the logistics industry as the key link connecting production and consumption, its operation efficiency, safety and transparency play a decisive role in the stability and development of the entire supply chain. Accurate, complete and tamper-proof tracking of the status of goods during circulation has become a core requirement. To meet this challenge, blockchain technology, which is characterized by decentralization, data encryption and tamper resistance, is widely regarded as an ideal technical cornerstone for building a new generation of trusted logistics traceability system. The application of blockchain technology in the logistics field aims to fundamentally solve the problems of information silos, data tampering and lack of trust faced by traditional centralized databases by establishing a distributed ledger jointly maintained by all participants.

[0003] However, with the continuous development of related technologies and the increasingly stringent requirements of application scenarios on traceability granularity and security level, the existing technology with logistics nodes as the triggering mechanism has some inherent characteristics at the principle level. The existing technology usually regards the packaging container itself as an information opaque "black box". The core idea of this model is that as long as the records between two consecutive logistics nodes are complete, the status of the package during this period is safe. However, during transportation, the packaging box may be illegally opened and the internal goods may be replaced and resealed. This series of core state changes related to the safety of the goods body are completely outside the scope of the blockchain record because no "node event" has been triggered. Ultimately, the blockchain presents a seemingly perfect circulation record, but the physical entity it points to may have completely changed its appearance and thus cannot guarantee end-to-end physical credibility. SUMMARY

[0004] The present application aims to provide a logistics packaging traceability data transmission system and method based on a blockchain to solve the problems in the prior art.

[0005] To achieve the above-mentioned purpose, the present application provides the following technical solution: a logistics packaging traceability data transmission method based on a blockchain, the method comprising:

[0006] Step S100: Collecting the original external surface information of the logistics packaging, establishing a height field matrix according to the height difference between the three-dimensional point cloud data and the mean value of the logistics packaging, and obtaining a filter response matrix of the height field matrix through a filter bank;

[0007] Step S200: converting each filter response matrix into a binary sequence string and splicing into a binary feature code, repeatedly generating a binary feature code, forming a feature code sequence by extracting invariant bits, and then calculating the original fingerprint through hash calculation;

[0008] Step S300: generating an error correction code containing a check bit based on the feature code sequence, constructing a data body containing identity coding, an original fingerprint, error correction auxiliary data, and a timestamp, and broadcasting to the blockchain after elliptical curve digital signature;

[0009] Step S400: obtaining the current surface feature and processing to obtain the current feature code sequence, correcting the current state information and calculating the current fingerprint in combination with the error correction auxiliary data queried in the blockchain, and determining the package integrity by comparing with the original fingerprint;

[0010] Step S500: calculating the Hamming distance between the current fingerprint and the original fingerprint, generating a verification identifier in combination with the fingerprint comparison result and the relationship between the Hamming distance and the threshold, and generating a new data body containing the verification identifier and broadcasting to the blockchain.

[0011] Further, step S100 includes:

[0012] Step S101: scanning the original outer surface topography of the logistics package to obtain the original three-dimensional point cloud data of the logistics package;

[0013] Step S102: performing surface fitting on the original three-dimensional point cloud data through a polynomial fitting method to obtain an original reference surface, obtaining the vertical height of each point cloud data element in the original three-dimensional point cloud data, obtaining the vertical height difference between each point cloud data element and the vertical height of the original reference surface, and collecting the vertical height difference of the point cloud data element to obtain a height field matrix M;

[0014] Step S103: obtaining a group of Gabor filters composed of n two-dimensional Gabor filters, and performing convolution operation on the height field matrix M using the n Gabor filters to obtain n filter response matrices.

[0015] Further, step S200 includes:

[0016] Step S201: for each filter response matrix, calculating the mean value of all elements in the filter response matrix, comparing each element in the filter response matrix with the mean value, if the element value is greater than the mean value, generating a binary bit 1, if less than or equal to the mean value, generating a binary bit 0, and corresponding to each filter response matrix, generating a binary sequence string;

[0017] Step S202: splice all n binary sequence strings to obtain a binary feature code of the logistics package, repeat steps S101-S201 several times, obtain a binary feature code after each repetition, obtain bit positions with unchanged values in all binary feature codes, collect all values corresponding to the bit positions to form a feature code sequence;

[0018] Step S203: calculate the feature code sequence through a hash function to obtain an original fingerprint R initial .

[0019] By extracting the unchanged bit positions, the influence of noise or slight interference such as slight vibration and light change can be filtered, the feature stability is enhanced, the original fingerprint generated by the hash calculation has uniqueness and irreversibility, the security and uniqueness of the feature identifier are ensured, and the effectiveness of the comparison is facilitated.

[0020] Further, step S300 includes:

[0021] Step S301: take the feature code sequence as an information bit, generate an error correction code of the feature code sequence through a linear block code encoding method, the error correction code includes a check bit of the feature code sequence, and the check bit is taken as error correction auxiliary data;

[0022] Step S302: construct a data body, the data fields of the data body at least include: an identity code of the logistics package, the original fingerprint R initial , the error correction auxiliary data, and timestamp data;

[0023] Step S303: sign the data body through an elliptic curve digital signature algorithm to obtain complete identity information of the logistics package, and broadcast the complete identity information to a block chain.

[0024] Further, step S400 includes:

[0025] Step S401: obtain a current surface feature of the logistics package, repeat steps S101-S103 and steps S201-S202 to calculate a feature code sequence of the current logistics package, and take the feature code sequence of the current logistics package as current state information;

[0026] Step S402: obtain an identity code of the logistics package, query complete identity information in the block chain network according to the identity code, and obtain error correction auxiliary data and the original fingerprint R initial in the complete identity information;

[0027] Step S403: correct the current state information through the error correction auxiliary data to obtain current state correction information, calculate the current state correction information through the same hash algorithm as in step S203 to obtain a current fingerprint R corrected ;

[0028] Step S404: comparing the current fingerprint R corrected with the original fingerprint R initial , if the current fingerprint R corrected is completely same as the original fingerprint R initial , it is determined that the integrity of the logistics package is not damaged.

[0029] In combination with error correction decoding, the feature errors caused by measurement noise or environmental changes can be corrected, the accuracy of the current fingerprint calculation is improved, and through comparison with the original fingerprint, it can be accurately determined whether the package is damaged, thereby ensuring the reliability of the integrity verification.

[0030] Further, the step S500 comprises:

[0031] Step S501: calculating the Hamming distance Dh between the current fingerprint R corrected and the original fingerprint R nitial , obtaining the similarity difference threshold Ud, and generating a comparison result of Dh and Ud;

[0032] Step S502: if the current fingerprint R corrected is completely same as the original fingerprint R initial , a verification pass mark is generated; if the current fingerprint R corrected is different from the original fingerprint R initial , and Dh h ≤ Ud d , a verification risk mark is generated; if the current fingerprint R corrected is different from the original fingerprint R initial , and Dh h > Ud d , an alarm mark is generated.

[0033] Step S503: constructing a new data body, the data fields of the new data body at least comprising: the identity code of the logistics package, the pointing information, the verification mark and the current timestamp data;

[0034] The pointing information is a transaction hash pointing to the previous verification, the verification mark comprises the verification pass mark, the verification risk mark or the alarm mark, and the current timestamp data represents the time information of verifying the current state of the logistics package;

[0035] Step S504: signing the new data body by using the elliptic curve digital signature algorithm to obtain the updated identity information of the logistics package, and broadcasting the updated identity information to the block chain.

[0036] The Hamming distance quantifies the fingerprint difference, in combination with the threshold to generate multi-level verification marks, and realizes the fine evaluation of the package state; the new data body contains the pointing information and is chained, forming a continuous traceability chain, reducing the monitoring blind area, and improving the transparency and traceability of the whole traceability.

[0037] In order to better realize the above method, a logistics packaging traceability data transmission system based on a blockchain is also proposed, which comprises a surface feature acquisition module, an original fingerprint management module, an initial identity management module, a surface feature comparison module and an identity update module.

[0038] The surface feature acquisition module is used to collect the original external surface information of the logistics packaging, establish a height field matrix according to the height difference between the three-dimensional point cloud data and the mean value of the logistics packaging, and obtain a filter response matrix of the height field matrix through a filter bank;

[0039] The original fingerprint management module is used to convert each filter response matrix into a binary sequence string and splice it into a binary feature code, repeatedly generate a binary feature code, form a feature code sequence by extracting an invariant bit, and then calculate an original fingerprint through a hash calculation;

[0040] The initial identity management module is used to generate an error correction code containing a check bit based on the feature code sequence, construct a data body containing an identity code, an original fingerprint, error correction auxiliary data and a timestamp, and broadcast the data body to the blockchain after elliptical curve digital signature;

[0041] The surface feature comparison module is used to obtain the current surface feature and process it to obtain the current feature code sequence, correct the current state information in combination with the error correction auxiliary data queried in the blockchain and calculate the current fingerprint, and determine whether the packaging integrity is damaged by comparing the current fingerprint with the original fingerprint;

[0042] The identity update module is used to calculate the Hamming distance between the current fingerprint and the original fingerprint, generate a verification identifier in combination with the fingerprint comparison result and the relationship between the Hamming distance and the threshold, and broadcast a new data body containing the verification identifier to the blockchain.

[0043] Further, the surface feature acquisition module comprises a surface scanning unit, a height feature management unit and a filter response unit, wherein the surface scanning unit is used to scan the original external surface topography of the logistics packaging and obtain the original three-dimensional point cloud data of the logistics packaging; the height feature management unit is used to perform surface fitting on the original three-dimensional point cloud data through a polynomial fitting method to obtain an original reference surface, obtain the vertical height of each point cloud data element in the original three-dimensional point cloud data, obtain the vertical height difference between each point cloud data element and the original reference surface, and collect the vertical height difference of the point cloud data elements to obtain a height field matrix M; and the filter response unit is used to obtain a group of Gabor filters composed of n two-dimensional Gabor filters, and perform convolution operations on the height field matrix M with the n Gabor filters to obtain n filter response matrices.

[0044] Further, the original fingerprint management module comprises: a binary sequence string generation unit, a feature code sequence management unit and an original fingerprint generation unit. The binary sequence string generation unit is configured to calculate the mean of all elements in each filter response matrix, compare each element in the filter response matrix with the mean, generate a binary bit 1 if the element value is greater than the mean, and generate a binary bit 0 if the element value is less than or equal to the mean, and generate a binary sequence string corresponding to each filter response matrix. The feature code sequence management unit is configured to splice all binary sequence strings to obtain a binary feature code of the logistics package. After repeating several times, a binary feature code is obtained each time. The bit positions with unchanged values in all binary feature codes are obtained, and all values corresponding to the bit positions are collected to form a feature code sequence. The original fingerprint generation unit is configured to calculate the feature code sequence through a hash function to obtain an original fingerprint.

[0045] Further, the initial identity management module comprises: an error correction auxiliary data management unit, an original data body management unit and an identity information broadcast unit. The error correction auxiliary data management unit is configured to generate an error correction code of the feature code sequence by a linear block code encoding method, wherein the error correction code comprises a check bit of the feature code sequence, and the check bit is used as error correction auxiliary data. The original data body management unit is configured to construct a data body, wherein the data fields of the data body at least comprise an identity code of the logistics package, an original fingerprint, error correction auxiliary data and timestamp data. The identity information broadcast unit is configured to sign the data body through an elliptic curve digital signature algorithm to obtain complete identity information of the logistics package, and broadcast the complete identity information to a block chain.

[0046] Further, the surface feature comparison module comprises: a current state information management unit, a comparison information acquisition unit, a current fingerprint management unit and an information comparison unit. The current state information management unit is configured to obtain the current surface feature of the logistics package, calculate the feature code sequence of the current logistics package, and record the feature code sequence of the current logistics package as the current state information. The comparison information acquisition unit is configured to obtain the identity code of the logistics package, query the complete identity information in the block chain network according to the identity code, and obtain the error correction auxiliary data and the original fingerprint in the complete identity information. The current fingerprint management unit is configured to correct the current state information through the error correction auxiliary data to obtain current state correction information, and calculate the current state correction information through a hash algorithm to obtain a current fingerprint. The information comparison unit is configured to compare the current fingerprint with the original fingerprint. If the current fingerprint is exactly the same as the original fingerprint, it is determined that the integrity of the logistics package has not been damaged.

[0047] Further, the identity updating module comprises a difference degree calculation unit, a comparison representation management unit, a new data body management unit and an identity information updating unit, wherein the difference degree calculation unit is configured to calculate the Hamming distance between the current fingerprint and the original fingerprint, obtain a similarity difference threshold, and generate a comparison result of the comparison between the Hamming distance and the difference threshold; the comparison representation management unit is configured to generate a verification pass identifier when the current fingerprint is completely identical to the original fingerprint; generate a verification risk identifier when the current fingerprint is different from the original fingerprint and the Hamming distance is less than or equal to the difference threshold; and generate an alarm identifier when the current fingerprint is different from the original fingerprint and the Hamming distance is greater than the difference threshold; the new data body management unit is configured to construct a new data body, and the data fields of the new data body at least comprise an identity code of the logistics package, pointing information, a verification identifier and current timestamp data; and the identity information updating unit is configured to sign the new data body by using an elliptic curve digital signature algorithm to obtain updated identity information of the logistics package, and broadcast the updated identity information to a block chain.

[0048] Compared with the prior art, the beneficial effects of the present application are that the method adopted by the present application successfully converts a physical tampering event that cannot be found in a traditional traceability system into a digital alarm event that can be found immediately, quantified accurately and traced permanently on a block chain by deeply binding the physical integrity of the package with the block chain data, thereby fundamentally solving the technical problem of data credibility but physical suspicion, and improving the security, granularity and overall credibility of logistics traceability. BRIEF DESCRIPTION OF DRAWINGS

[0049] Fig. 1 FIG. 1 is a structural schematic diagram of a logistics package traceability data transmission system based on a block chain according to the present application;

[0050] Fig. 2 FIG. 2 is a flowchart of a logistics package traceability data transmission method based on a block chain according to the present application. DETAILED DESCRIPTION

[0051] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0052] Embodiment: As shown in the figure, the present application provides a technical solution, a logistics package traceability data transmission system and method based on a block chain. Figs. 1-2

[0053] ​Step S100: Collecting original outer surface information of the logistics package, establishing a height field matrix according to the height difference between the three-dimensional point cloud data and the mean value of the logistics package, and obtaining a filter response matrix of the height field matrix through a filter set;

[0054] The step S100 comprises:

[0055] Step S101: Scanning the original outer surface topography of the logistics package to obtain original three-dimensional point cloud data of the logistics package;

[0056] Step S102: performing surface fitting on the original three-dimensional point cloud data through a polynomial fitting method to obtain an original reference surface, obtaining the vertical height of each point cloud data element in the original three-dimensional point cloud data, obtaining the vertical height difference between each point cloud data element and the original reference surface, and collecting the vertical height difference of the point cloud data element to obtain a height field matrix M.

[0057] Step S103: obtaining a set of Gabor filters composed of n two-dimensional Gabor filters, and performing convolution operation on the height field matrix M using the n Gabor filters to obtain n filter response matrices.

[0058] In the embodiment, a set of two-dimensional Gabor filters is used to perform convolution operation on the height field matrix M. The set of two-dimensional Gabor filters is composed of 6 directions θ = 0°, 30°, 60°, 90°, 120°, 150° and 4 scales λ = 2, 4, 8, 16, a total of 24 independent filters. The parameters of each Gabor filter include G(x, y; λ, θ, ψ, σ, γ), wherein (x, y) represents the position of the filter in the height field matrix M, λ is the wavelength of the sine factor, θ is the filter direction, ψ is the phase offset, which is set to π / 2 in the embodiment, σ is the standard deviation of the Gaussian envelope, and γ is the spatial aspect ratio, which is set to 0.5 in the embodiment.

[0059] Step S200: converting each filter response matrix into a binary sequence string and splicing it into a binary feature code, repeatedly generating a binary feature code, forming a feature code sequence by extracting an invariant bit, and then calculating the original fingerprint through a hash calculation;

[0060] The step S200 comprises:

[0061] Step S201: For each filter response matrix, calculate the mean value of all elements in the filter response matrix, compare each element in the filter response matrix with the mean value, if the element value is greater than the mean value, generate a binary bit 1, if less than or equal to the mean value, generate a binary bit 0, and generate a binary sequence string corresponding to each filter response matrix;

[0062] Step S202: concatenate all n binary sequence strings to obtain a binary feature code of the logistics package, repeat steps S101-S201 several times, obtain a binary feature code after each repetition, obtain bit positions with unchanged values in all binary feature codes, collect all values corresponding to the bit positions to form a feature code sequence;

[0063] Step S203: calculate the feature code sequence through a hash function to obtain an original fingerprint R initial .

[0064] In an embodiment, a local feature of the logistics package, such as a seam or an opening, can be modeled specifically, at least 3 measurements are taken at the same local feature position, at least 3 binary feature codes are generated, binary bits with unchanged values in the bit positions are screened out to form a feature sequence code, and the feature sequence code is converted into an original fingerprint through a hash algorithm such as the SHA-256 algorithm.

[0065] Step S300: generate an error correction code containing a check bit based on the feature code sequence, construct a data body containing an identity code, an original fingerprint, error correction auxiliary data, and a timestamp, and broadcast the data body to a blockchain after elliptical curve digital signature;

[0066] Step S300 includes:

[0067] Step S301: generate an error correction code of the feature code sequence through a linear block code encoding method by taking the feature code sequence as information bits, the error correction code includes check bits of the feature code sequence, and the check bits are taken as error correction auxiliary data;

[0068] Step S302: construct a data body, the data fields of the data body at least include: an identity code of the logistics package, an original fingerprint R initial , error correction auxiliary data, and timestamp data;

[0069] Step S303: sign the data body through an elliptical curve digital signature algorithm to obtain complete identity information of the logistics package, and broadcast the complete identity information to a blockchain.

[0070] In an embodiment, a BCH (Bose-Chaudhuri-Hocquenghem) encoding scheme is adopted, a BCH(n, k, t) code is used, where n is the length of the encoded code word, k is the length of the original information, i.e., the length of the feature code sequence, and t is the number of correctable error bits, the feature code sequence is taken as information bits, n-k check bits are calculated through a BCH encoding generator polynomial to serve as error correction auxiliary data, denoted as H_data, which is the n-k check bits;

[0071] The signed complete transaction is broadcast to the blockchain network, and the consensus nodes in the network verify the signature and perform a consensus algorithm, such as Byzantine Fault Tolerant PBFT, to package the complete identity information into a new block as a genesis transaction, thereby completing the firm binding of physical packaging and digital identity.

[0072] Step S400: Obtain the current surface feature and process to obtain the current feature code sequence, correct the current state information in combination with the error correction auxiliary data queried in the blockchain, and calculate the current fingerprint. By comparing with the original fingerprint, the integrity of the package is determined.

[0073] Step S400 includes:

[0074] Step S401: Obtain the current surface feature of the logistics package, repeat steps S101-S103 and steps S201-S202 to calculate the feature code sequence of the current logistics package, and record the feature code sequence of the current logistics package as the current state information.

[0075] Step S402: Obtain the identity code of the logistics package, and obtain the error correction auxiliary data and the original fingerprint R initial from the complete identity information queried in the blockchain network according to the identity code.

[0076] Step S403: Correct the current state information by the error correction auxiliary data to obtain the current state correction information, and calculate the current state correction information by using the same hash algorithm as in step S203 to obtain the current fingerprint R corrected .

[0077] Step S404: Compare the current fingerprint R corrected with the original fingerprint R initial . If the current fingerprint R corrected is exactly the same as the original fingerprint R initial , it is determined that the integrity of the logistics package has not been damaged.

[0078] The current state information is combined with the error correction auxiliary data to run the BCH decoding algorithm. The BCH decoder uses H_data as the check information to identify and correct the potential error bits in the current state information, such as error bits caused by image errors due to minor measurement noise or environmental changes.

[0079] The corrected current state correction information is executed by the SHA-256 algorithm to convert the current state correction information into the current fingerprint, which is compared with the original fingerprint obtained.

[0080] Step S500: Calculate the Hamming distance between the current fingerprint and the original fingerprint, combine the fingerprint comparison result and the relationship between the Hamming distance and the threshold, generate a verification identifier, generate a new data body containing the verification identifier and broadcast it to the blockchain;

[0081] Wherein, step S500 comprises:

[0082] Step S501: Calculate the Hamming distance Dh between the current fingerprint R corrected and the original fingerprint Ri nitial , obtain the similarity difference threshold Ud, and generate a comparison result of Dh and Ud;

[0083] Step S502: If the current fingerprint R corrected is exactly the same as the original fingerprint R initial , generate a verification pass identifier; if the current fingerprint R corrected is different from the original fingerprint R initial , and Dh h ≤ Ud d , generate a verification risk identifier; if the current fingerprint R corrected is different from the original fingerprint R initial , and Dh h > Ud d , generate an alarm identifier;

[0084] Step S503: Construct a new data body, and the data fields of the new data body at least include: the identity code of the logistics package, the pointing information, the verification identifier, and the current timestamp data;

[0085] The pointing information is the transaction hash pointing to the previous verification, the verification identifier includes the verification pass identifier, the verification risk identifier, or the alarm identifier, and the current timestamp data represents the time information of verifying the current state of the logistics package;

[0086] Step S504: Sign the new data body through the elliptic curve digital signature algorithm to obtain the updated identity information of the logistics package, and broadcast the updated identity information to the blockchain.

[0087] In an embodiment, the current fingerprint R corrected and the original fingerprint R initial are obtained as follows: wherein, i represents a binary bit, represents a binary symbol in the i-th binary bit of the current fingerprint R corrected , represents a binary symbol in the i-th binary bit of the original fingerprint R initial , represents the exclusive or operation;

[0088] In an embodiment, a traceable verification process is formed by transaction hash, assisted by forming a traceable chain to reduce the monitoring blind area.

[0089] An embodiment provides a complete process of the above method:

[0090] 1. Packaging and Genesis: At the packaging line at A, an anti-counterfeiting tape is pasted on the sealing of each logistics package. The surface feature acquisition collects the three-dimensional topography of a 15mm x 15mm area at the junction of the anti-counterfeiting tape and the carton. Through Gabor filtering and encoding process, an initial original fingerprint R initial is generated, and a BCH error correction auxiliary data H_data is calculated. A genesis transaction containing PackageID "SN-73451", original fingerprint R initial and H_data is signed and recorded on the block height 2,014,531 of the goods supply chain alliance chain.

[0091] 2. Departure verification: Before the goods are loaded from the packaging line, the warehouse administrator uses a handheld mobile verification terminal to scan the packaging box. The terminal generates the first challenge fingerprint R corrected1 , obtains the original fingerprint R initial and H_data from the chain, and finds that the hash values are completely matched after local decoding correction. The terminal generates a complete integrity authentication transaction of "verification passed identification", containing geographic location, timestamp, administrator ID, etc., and broadcasts it on the chain, linked to the genesis transaction.

[0092] 3. Midway inspection: The goods are transported to a transit hub in transit, and the supervisory agency personnel conduct inspection. The same packaging box is scanned using the official mobile verification terminal equipped. At this time, due to normal temperature and humidity changes and slight vibration during transportation, the collected topography is slightly different. The terminal generates the second current feature code, which is directly converted into the second challenge fingerprint R corrected2 , which is different from the original fingerprint R initial . After BCH decoder correction using H_data, the second current feature code corresponding to the current state correction information is obtained, and the hash value of the current state correction information is the original fingerprint R initial . The Hamming distance between R corrected2 and R initial is calculated to be 15, which is less than the similarity difference threshold of 30, within the safety threshold. A new "verification risk identification" authentication transaction is recorded on the chain, proving that the physical state of the goods is intact at this transit node.

[0093] 4. Scenario Tampering: In the final transportation segment from the transit hub to point B, criminals intercept transport vehicles and attempt to switch the goods inside the logistics packaging. For example, they carefully use a heat gun to peel off the sealing tape, replace the internal items, and then use strong glue to re-attach the original tape. Although it appears seamless to the naked eye, this process causes irreversible damage to the fiber structure of the tape itself, the microscopic morphology of the cured glue, and the fiber layer on the surface of the underlying cardboard box.

[0094] 5. Goods Arrival and Inspection: Goods are delivered to point B, the final integrity verification is performed using a mobile verification terminal according to standard procedures before warehousing. The terminal scan generates a third current fingerprint; however, due to severe physical damage, even after the BCH decoder attempts error correction, the current state correction information corresponding to the third current fingerprint, obtained through a hash algorithm, fails to produce the third challenge fingerprint R. corrected3 Also with the original fingerprint R initial The difference is significant. Simultaneously, the calculated Hamming distance spikes to 197, far exceeding the threshold of 30. The terminal immediately identifies this as an "alarm flag" and displays a red warning on the screen. An integrity-verified transaction, including the "alarm flag" status, a Hamming distance of 197, and the endpoint location and timestamp at point B, is automatically generated and broadcast onto the blockchain.

[0095] The system includes: a surface feature acquisition module, a raw fingerprint management module, an initial identity management module, a surface feature comparison module, and an identity update module;

[0096] The surface feature acquisition module is used to collect the original outer surface information of the logistics packaging. It establishes a height field matrix based on the height difference between the 3D point cloud data and the mean height of the logistics packaging, and obtains the filter response matrix of the height field matrix through a filter bank. The surface feature acquisition module includes a surface scanning unit, a height feature management unit, and a filter response unit. The surface scanning unit scans the original outer surface morphology of the logistics packaging to acquire the original 3D point cloud data. The height feature management unit performs surface fitting on the original 3D point cloud data using a polynomial fitting method to obtain the original reference surface, acquires the vertical height of each point cloud data element, and obtains the difference between the vertical height of each point cloud data element and the vertical height of the original reference surface. These vertical height differences are then aggregated to obtain the height field matrix M. The filter response unit acquires n two-dimensional Gabor filters to form a Gabor filter bank, and performs convolution operations on the height field matrix M using the n Gabor filter banks to obtain n filter response matrices.

[0097] The original fingerprint management module is used to convert each filter response matrix into a binary sequence string and splice it into a binary feature code. The binary feature code is repeatedly generated by forming a feature code sequence through extracting invariant bits, and then the original fingerprint is obtained through hash calculation. The original fingerprint management module includes a binary sequence string generation unit, a feature code sequence management unit, and an original fingerprint generation unit. The binary sequence string generation unit is used to calculate the mean value of all elements in each filter response matrix, compare each element in the filter response matrix with the mean value, generate binary bit 1 if the element value is greater than the mean value, and generate binary bit 0 if the element value is less than or equal to the mean value, and generate a binary sequence string corresponding to each filter response matrix. The feature code sequence management unit is used to splice all binary sequence strings to obtain the binary feature code of the logistics package. After repeating several times, a binary feature code is obtained each time. The bit positions whose values remain unchanged in all binary feature codes are obtained, all values corresponding to the bit positions are collected to form a feature code sequence. The original fingerprint generation unit is used to calculate the feature code sequence through a hash function to obtain the original fingerprint.

[0098] The initial identity management module is used to generate an error correction code containing a check bit based on the feature code sequence, construct a data body containing an identity code, an original fingerprint, error correction auxiliary data, and a timestamp, and broadcast the data body signed by an elliptic curve digital signature to a blockchain. The initial identity management module includes an error correction auxiliary data management unit, an original data body management unit, and an identity information broadcast unit. The error correction auxiliary data management unit is used to generate the error correction code of the feature code sequence by taking the feature code sequence as the information bit through the linear block code encoding method. The error correction code includes the check bit of the feature code sequence, and the check bit is used as the error correction auxiliary data. The original data body management unit is used to construct the data body. The data fields of the data body include at least the identity code, the original fingerprint, the error correction auxiliary data, and the timestamp data of the logistics package. The identity information broadcast unit is used to sign the data body through the elliptic curve digital signature algorithm to obtain the complete identity information of the logistics package, and broadcast the complete identity information to the blockchain.

[0099] The surface feature comparison module is used to obtain the current surface feature and process the current feature code sequence, correct the current state information in combination with the error correction auxiliary data queried in the blockchain, and calculate the current fingerprint. By comparing with the original fingerprint, it is determined whether the packaging integrity is damaged, wherein the surface feature comparison module comprises a current state information management unit, a comparison information acquisition unit, a current fingerprint management unit and an information comparison unit, wherein the current state information management unit is used to obtain the current surface feature of the logistics packaging, calculate the feature code sequence of the current logistics packaging, and record the feature code sequence of the current logistics packaging as the current state information; the comparison information acquisition unit is used to obtain the identity code of the logistics packaging, query the complete identity information in the blockchain network according to the identity code, obtain the error correction auxiliary data and the original fingerprint in the complete identity information; the current fingerprint management unit is used to correct the current state information by the error correction auxiliary data to obtain the current state correction information, calculate the current state correction information by using the hash algorithm to obtain the current fingerprint; the information comparison unit is used to compare the current fingerprint with the original fingerprint. If the current fingerprint is exactly the same as the original fingerprint, it is determined that the integrity of the logistics packaging has not been damaged;

[0100] The identity updating module is used to calculate the Hamming distance between the current fingerprint and the original fingerprint, generate a verification identifier in combination with the fingerprint comparison result and the relationship between the Hamming distance and the threshold, and broadcast a new data body containing the verification identifier to the blockchain, wherein the identity updating module comprises a difference degree calculation unit, a comparison representation management unit, a new data body management unit and an identity information updating unit, wherein the difference degree calculation unit is used to calculate the Hamming distance between the current fingerprint and the original fingerprint, obtain the similarity difference threshold, and generate a comparison result of comparing the Hamming distance and the difference threshold; the comparison representation management unit is used to generate a verification pass identifier when the current fingerprint is exactly the same as the original fingerprint; generate a verification risk identifier when the current fingerprint is different from the original fingerprint and the Hamming distance is less than or equal to the difference threshold; generate an alarm identifier when the current fingerprint is different from the original fingerprint and the Hamming distance is greater than the difference threshold; the new data body management unit is used to construct a new data body, and the data fields of the new data body at least include the identity code of the logistics packaging, the pointing information, the verification identifier and the current timestamp data; the identity information updating unit is used to sign the new data body by using the elliptic curve digital signature algorithm to obtain the updated identity information of the logistics package, and broadcast the updated identity information to the blockchain.

[0101] It will be apparent to those skilled in the art that the application is not limited to the details of the above-exemplified embodiments and that the present application can be implemented in other particular forms without departing from the spirit or essential characteristics of the present application. The embodiments should therefore be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the above description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. No reference signs in the claims should be considered as limiting the scope of the claims with respect to the figures of the application.

Claims

1. A blockchain-based logistics packaging traceability data transmission method, characterized in that: The method comprises the steps of: Step S100: Collecting the original outer surface information of the logistics package, establishing a height field matrix according to the height difference of the three-dimensional point cloud data and the mean value of the logistics package, and obtaining a filter response matrix of the height field matrix through a filter set; Step S200: Transforming each filter response matrix into a binary sequence string and splicing it into a binary feature code, repeatedly generating a binary feature code, forming a feature code sequence by extracting constant bits, and then calculating an original fingerprint through a hash calculation; Step S300: Generating an error correction code containing a check bit based on the feature code sequence, constructing a data body containing an identity code, an original fingerprint, error correction auxiliary data and a timestamp, and broadcasting the data body to the blockchain after elliptical curve digital signature; Step S400: Obtaining the current surface feature and processing to obtain the current feature code sequence, combining the error correction auxiliary data queried in the blockchain to correct the current state information and calculate the current fingerprint, and determining the package integrity by comparing with the original fingerprint; Step S500: Calculating the Hamming distance between the current fingerprint and the original fingerprint, combining the fingerprint comparison result and the relationship between the Hamming distance and the threshold, generating a verification identifier, and generating a new data body containing the verification identifier and broadcasting it to the blockchain.

2. The blockchain-based logistics packaging traceability data transmission method according to claim 1, characterized in that: Step S100 comprises: Step S101: Scanning the original outer surface topography of the logistics package to obtain original three-dimensional point cloud data of the logistics package; Step S102: performing surface fitting on the original three-dimensional point cloud data through a polynomial fitting method to obtain an original reference surface, obtaining the vertical height of each point cloud data element in the original three-dimensional point cloud data, obtaining the vertical height difference of each point cloud data element and the original reference surface, and collecting the vertical height difference of the point cloud data elements to obtain a height field matrix M; Step S103: obtaining a group of Gabor filter sets composed of n two-dimensional Gabor filters, and performing convolution operation on the height field matrix M with the n Gabor filter sets to obtain n filter response matrices.

3. The blockchain-based logistics packaging traceability data transmission method according to claim 2, characterized in that: Step S200 comprises: Step S201: For each filter response matrix, calculate the mean value of all elements in the filter response matrix, compare each element in the filter response matrix with the mean value, if the element value is greater than the mean value, generate a binary bit 1, if it is less than or equal to the mean value, generate a binary bit 0, and generate a binary sequence string corresponding to each filter response matrix; Step S202: Splice all n binary sequence strings to obtain the binary feature code of the logistics package, repeat steps S101-S201 several times, obtain a binary feature code after each repetition, obtain the bit positions whose values remain unchanged in all binary feature codes, collect all values corresponding to the bit positions to form a feature code sequence; Step S203: Calculate the feature code sequence through a hash function to obtain the original fingerprint R initial .

4. The blockchain-based logistics packaging traceability data transmission method according to claim 3, characterized in that: Step S300 comprises: Step S301: Taking the feature code sequence as the information bit, generating the error correction code of the feature code sequence through the linear block code encoding method, the error correction code including the check bit of the feature code sequence, and taking the check bit as the error correction auxiliary data; Step S302: constructing a data body, data fields of the data body at least including: identity code of the logistics package, original fingerprint R initial , error correction auxiliary data and timestamp data; Step S303: signing the data body through the elliptical curve digital signature algorithm to obtain the complete identity information of the logistics package, and broadcasting the complete identity information to the blockchain.

5. The blockchain-based logistics packaging traceability data transmission method according to claim 4, characterized in that: Step S400 comprises: Step S401: obtaining the current surface feature of the logistics package, repeating steps S101-S103 and steps S201-S202 to calculate the feature code sequence of the current logistics package, and recording the feature code sequence of the current logistics package as the current state information; Step S402: Obtain the identity code of the logistics package, query the complete identity information in the blockchain network according to the identity code, obtain the error correction auxiliary data and the original fingerprint R in the complete identity information initial ; Step S403: correcting the current state information by error correction auxiliary data to obtain current state correction information, and using the same hash algorithm as in step S203 to calculate the current state correction information to obtain the current fingerprint R corrected ; Step S404: compare the current fingerprint R corrected with the original fingerprint R initial The current fingerprint R corrected with the original fingerprint R initial is exactly the same, then it is determined that the integrity of the logistics packaging has not been compromised.

6. The blockchain-based logistics packaging traceability data transmission method according to claim 5, characterized in that: Step S500 comprises: Step S501: calculate the current fingerprint R corrected and the Hamming distance Dh of the original fingerprint Ri nitial , obtain the similarity difference threshold Ud, and generate a comparison result of the comparison between Dh and Ud; Step S502: Current fingerprint R corrected is the same as the original fingerprint R initial , a verification pass identification is generated; the current fingerprint R corrected is different from the original fingerprint R initial , and D h ≤ U d , a verification risk identification is generated; the current fingerprint R corrected is different from the original fingerprint R initial , and D h > U d , an alarm identification is generated; Step S503: constructing a new data body, wherein the data fields of the new data body at least include the identity code of the logistics package, the pointing information, the verification identifier and the current timestamp data; The pointing information is a transaction hash pointing to the previous verification, the verification identifier includes a verification pass identifier, a verification risk identifier or an alarm identifier, and the current timestamp data represents the time information of verifying the current state of the logistics package; Step S504: signing the new data body by using an elliptic curve digital signature algorithm to obtain updated identity information of the logistics package, and broadcasting the updated identity information to a block chain. 7.A blockchain-based logistics package traceability data transmission system for performing the blockchain-based logistics package traceability data transmission method of any one of claims 1-6. The system comprises: A surface feature acquisition module, an original fingerprint management module, an initial identity management module, a surface feature comparison module and an identity updating module; The surface feature acquisition module is configured to collect original external surface information of the logistics package, establish a height field matrix according to a height difference between three-dimensional point cloud data and a mean value of the logistics package, and obtain a filter response matrix of the height field matrix by using a filter bank; The original fingerprint management module is configured to convert each filter response matrix into a binary sequence string and splice the binary sequence string into a binary feature code, repeatedly generate the binary feature code, form a feature code sequence by extracting an invariable bit, and calculate an original fingerprint by using a hash algorithm; The initial identity management module is configured to generate an error correction code containing a check bit based on the feature code sequence, construct a data body containing an identity code, an original fingerprint, error correction auxiliary data and a timestamp, broadcast the data body to the block chain after elliptic curve digital signature, and the like; The surface feature comparison module is configured to obtain a current surface feature and process the current surface feature to obtain a current feature code sequence, correct current state information in combination with error correction auxiliary data queried in the block chain and calculate a current fingerprint, and determine whether the integrity of the package is damaged by comparing the current fingerprint with the original fingerprint; The identity updating module is configured to calculate a Hamming distance between the current fingerprint and the original fingerprint, generate a verification identifier in combination with a fingerprint comparison result and a relationship between the Hamming distance and a threshold, and broadcast a new data body containing the verification identifier to the block chain.

8. The logistics package traceability data transmission system based on the block chain according to claim 7, wherein: The surface feature acquisition module comprises a surface scanning unit, a height feature management unit and a filtering response unit, wherein the surface scanning unit is configured to scan the original outer surface topography of the logistics package and acquire original three-dimensional point cloud data of the logistics package; the height feature management unit is configured to perform surface fitting on the original three-dimensional point cloud data by a polynomial fitting method to obtain an original reference surface, acquire the vertical height of each point cloud data element in the original three-dimensional point cloud data, acquire the vertical height difference between each point cloud data element and the original reference surface, and collect the vertical height difference of the point cloud data elements to obtain a height field matrix M; and the filtering response unit is configured to acquire a group of Gabor filters composed of n two-dimensional Gabor filters, perform convolution operations on the height field matrix M by using the n Gabor filters, and obtain n filtering response matrices; The original fingerprint management module comprises a binary sequence string generation unit, a feature code sequence management unit and an original fingerprint generation unit, wherein the binary sequence string generation unit is configured to calculate the mean value of all elements in each filtering response matrix, compare each element in the filtering response matrix with the mean value, generate a binary bit 1 if the element value is greater than the mean value, generate a binary bit 0 if the element value is less than or equal to the mean value, and generate a binary sequence string corresponding to each filtering response matrix; the feature code sequence management unit is configured to splice all the binary sequence strings to obtain a binary feature code of the logistics package, obtain a binary feature code after repeating several times, acquire the bit positions with unchanged values in all the binary feature codes, collect all the values corresponding to the bit positions to form a feature code sequence; and the original fingerprint generation unit is configured to calculate the feature code sequence by using a hash function to obtain an original fingerprint.

9. The logistics package traceability data transmission system based on the blockchain according to claim 7, characterized in that: The initial identity management module comprises an error correction auxiliary data management unit, an original data body management unit and an identity information broadcast unit, wherein the error correction auxiliary data management unit is configured to generate an error correction code of the feature code sequence by using a linear block code encoding method, wherein the error correction code comprises a check bit of the feature code sequence, and the check bit is used as error correction auxiliary data; the original data body management unit is configured to construct a data body, wherein the data fields of the data body at least include an identity code of the logistics package, an original fingerprint, error correction auxiliary data and timestamp data; and the identity information broadcast unit is configured to sign the data body by using an elliptic curve digital signature algorithm to obtain complete identity information of the logistics package, and broadcast the complete identity information to the blockchain. The surface feature comparison module comprises a current state information management unit, a comparison information acquisition unit, a current fingerprint management unit and an information comparison unit, wherein the current state information management unit is configured to obtain the current surface feature of the logistics package, calculate the feature code sequence of the current logistics package, and record the feature code sequence of the current logistics package as the current state information; the comparison information acquisition unit is configured to obtain the identity code of the logistics package, query the complete identity information in the blockchain network according to the identity code, obtain the error correction auxiliary data and the original fingerprint in the complete identity information; the current fingerprint management unit is configured to correct the current state information by using the error correction auxiliary data to obtain the current state correction information, calculate the current state correction information by using a hash algorithm to obtain the current fingerprint; and the information comparison unit is configured to compare the current fingerprint with the original fingerprint, and determine that the integrity of the logistics package is not damaged when the current fingerprint is completely the same as the original fingerprint.

10. The logistics package traceability data transmission system based on the blockchain according to claim 7, characterized in that: The identity updating module comprises a difference degree calculation unit, a comparison representation management unit, a new data body management unit and an identity information updating unit, wherein the difference degree calculation unit is configured to calculate the Hamming distance between the current fingerprint and the original fingerprint, obtain a similarity difference threshold, and generate a comparison result of the comparison Hamming distance and the difference threshold; the comparison representation management unit is configured to generate a verification pass identification when the current fingerprint is completely the same as the original fingerprint; generate a verification risk identification when the current fingerprint is different from the original fingerprint and the Hamming distance is less than or equal to the difference threshold; and generate an alarm identification when the current fingerprint is different from the original fingerprint and the Hamming distance is greater than the difference threshold; the new data body management unit is configured to construct a new data body, and the data fields of the new data body at least comprise the identity code of the logistics package, the pointing information, the verification identification and the current timestamp data; and the identity information updating unit is configured to sign the new data body by using an elliptic curve digital signature algorithm to obtain the updated identity information of the logistics package, and broadcast the updated identity information to the blockchain.

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