Electronic seal and digital signature authentication method for paperless customs clearance of cross-border trade

Abstract

The present application relates to the electronic seal and digital signature authentication method of paperless customs clearance of cross-border trade, relates to the technical field of industrial data management, and includes: the cargo station system sends the export cargo warehouse withdrawal and scene withdrawal application message to the aviation logistics platform; the aviation logistics platform sends the export cargo warehouse withdrawal and scene withdrawal application message to the air intelligent system; the aviation logistics platform receives the receipt of the air intelligent system and enters the warehouse; if the receipt is successful, the aviation logistics platform generates a pdf file according to the business message content, calls the signing server to sign the pdf file; the signing server uses the certificate hosted by the cargo station system to sign the pdf file, and returns the signed pdf file to the aviation logistics platform; the aviation logistics platform pushes the signed pdf file to the cargo station system, which has the advantage of improving the efficiency of export cargo warehouse withdrawal and scene withdrawal.

Description

Technical Field

[0001] This invention relates to the field of industrial data management technology, and in particular to an electronic seal and digital signature authentication method for paperless customs clearance in cross-border trade. Background Technology

[0002] With the rapid development of information technology, various industries have built corresponding business systems by connecting computer devices through networks, transferring the original offline business information to online business systems for processing, and effectively improving the efficiency of business information processing.

[0003] Traditional export cargo return applications rely on documents such as proof of inventory, explanations of non-compliance with shipping requirements, and application forms. These documents require manual stamping, signing, and offline transmission, leading to the following problems: document circulation involves multiple parties, including cargo stations, freight forwarders, customs, and airlines, with an average customs clearance time of 48-72 hours; the printing, storage, and manual verification of paper documents cost enterprises over ten million yuan annually; paper documents are easily altered or lost, and it is difficult to trace operational responsibility, which can easily lead to trade disputes.

[0004] Therefore, it is necessary to provide electronic seals and digital signature authentication methods for paperless customs clearance in cross-border trade to improve the efficiency of returning exported goods to warehouses. Summary of the Invention

[0005] This invention provides an electronic seal and digital signature authentication method for paperless customs clearance in cross-border trade, comprising: a cargo terminal system sending an application message for the return of exported goods to an air logistics platform; the air logistics platform sending the application message to an intelligent air transport system; the air logistics platform receiving a receipt from the intelligent air transport system and storing the goods in the warehouse; if the receipt indicates successful storage, the air logistics platform generating a PDF file based on the business message content and calling a signing server to sign the PDF file; the signing server using a certificate hosted by the cargo terminal system to sign the PDF file and returning the signed PDF file to the air logistics platform; and the air logistics platform pushing the signed PDF file back to the cargo terminal system.

[0006] Furthermore, the cargo station system is also used to: obtain the certificate information query request initiated by the user terminal corresponding to the export cargo return application message; and display the signature certificate information of the signed PDF file based on the certificate information query request.

[0007] Furthermore, the export goods return application message includes a message header and a message body; the message header includes a unique message code, a message function code, a message type, a sender code, a receiver code, a sending time, and a message version number; the message body includes a unique business message number, a file name, a file extension, a business type, and attachment data.

[0008] Furthermore, the cargo terminal system sends an application message for the return of exported goods to the air logistics platform, including: obtaining the historical message sending records of the cargo terminal system; fragmenting and encrypting the application message for the return of exported goods based on the historical message sending records of the cargo terminal system; and sending the fragmented and encrypted application message for the return of exported goods to the air logistics platform.

[0009] Furthermore, based on the historical message transmission records of the cargo terminal system, the export cargo return and withdrawal application messages are fragmented and encrypted, including: obtaining historical message transmission records of multiple other cargo terminal systems; calculating the message correlation coefficient between the cargo terminal system and other cargo terminal systems based on the historical message transmission records of the cargo terminal system and the historical message transmission records of multiple other cargo terminal systems; identifying similar other cargo terminal systems based on the message correlation coefficient between the cargo terminal system and other cargo terminal systems; obtaining the message transmission records of the cargo terminal system at multiple time points in the current period and the message transmission records of similar other cargo terminal systems at multiple time points in the current period, and predicting the message transmission demand of the cargo terminal system at multiple future time points in the current period; and fragmenting and encrypting the export cargo return and withdrawal application messages based on the message transmission demand of the cargo terminal system at multiple future time points in the current period.

[0010] Furthermore, based on the message sending requirements of the cargo terminal system at multiple future time points in the current period, the export cargo return and withdrawal application messages are fragmented and encrypted. This includes: establishing a multi-objective fragmentation optimization function; generating an optimal fragment size based on the message sending requirements of the cargo terminal system at multiple future time points in the current period, the file size of the export cargo return and withdrawal application messages, and the multi-objective fragmentation optimization function; performing a first fragmentation on the export cargo return and withdrawal application messages based on the optimal fragment size, generating multiple first data segments of the export cargo return and withdrawal application messages; for each first data segment, determining the risk value of the first data segment based on the variable fields included in the first data segment; determining whether to perform a second fragmentation on the first data segment based on the risk value of the first data segment; if so, performing a second fragmentation on the first data segment based on the risk value of the first data segment, generating multiple second data segments corresponding to the first data segment; and encrypting the fragmented export cargo return and withdrawal application messages.

[0011] Furthermore, the intelligent air transport system includes a computing power cluster, wherein the computing power cluster includes a computing power scheduling node and multiple message approval nodes. The computing power scheduling node is used to allocate message approval nodes for export cargo return and withdrawal application messages, and the message approval nodes are used to approve export cargo return and withdrawal application messages.

[0012] Furthermore, the computing power scheduling node is a message approval node for the export goods return and withdrawal application message, including: determining the message characteristics of the export goods return and withdrawal application message based on the business type, sending time and attachment data of the message header; obtaining the status information of each message approval node; and allocating a message approval node for the export goods return and withdrawal application message based on the message characteristics of the export goods return and withdrawal application message and the status information of each message approval node.

[0013] Furthermore, the message approval node is used to approve export goods return and withdrawal application messages, including: determining multiple preset approval rules corresponding to the export goods return and withdrawal application message; obtaining historical approval data; determining the review order of the multiple preset approval rules corresponding to the export goods return and withdrawal application message based on the historical approval data; and approving the export goods return and withdrawal application message according to the review order of the multiple preset approval rules corresponding to the export goods return and withdrawal application message.

[0014] Furthermore, the message approval node is also used to: assign reviewers based on the review results of multiple preset approval rules corresponding to the export goods return application message.

[0015] Compared to existing technologies, the electronic seal and digital signature authentication method for paperless customs clearance in cross-border trade provided in this specification has at least the following advantages:

[0016] 1. Through seamless integration of the cargo station system, air logistics platform, and intelligent air transport system, automatic message sending, automatic receipt reception and processing are achieved, reducing manual intervention and paper document transmission time. After receiving the successful warehousing receipt, the air logistics platform automatically generates a PDF file and calls the signing server to complete the electronic signature. The entire process is online, avoiding time-consuming steps such as traditional stamping and mailing, significantly improving customs clearance efficiency. The signing server digitally signs the PDF file to ensure that the content of the document is tamper-proof and the source is traceable, meeting the strict requirements of cross-border trade for data integrity and authenticity. The signing server uses a certificate hosted by the cargo station system for signing, realizing a strong association between the responsible party and the signature certificate, enhancing legal validity and compliance. The paperless process completely eliminates the costs of printing, storing, and transporting paper documents, which is especially suitable for high-frequency return and withdrawal scenarios, significantly reducing long-term operating costs.

[0017] 2. Traditional fixed-size fragmentation may lead to transmission congestion during peak hours or resource waste during off-peak hours, while dynamic fragmentation can match real-time network load, improve transmission efficiency, optimize fragment size based on demand prediction, reduce transmission failure rate caused by unreasonable fragmentation, reduce retransmission times and time costs, establish a fragmentation optimization model that comprehensively considers multiple dimensions such as packet size, transmission timeliness, and system load, generate the optimal fragment size, balance efficiency and resource consumption, and conduct risk assessment on data segments after the first fragmentation (such as variable fields containing sensitive information such as cargo value, destination, etc.), further subdivide high-risk segments, and reduce the risk of leakage of single segments;

[0018] 3. The computing power scheduling node dynamically allocates the optimal approval node based on message characteristics (business type, sending time, attachment data) and approval node status (load, processing capacity, historical performance). Traditional static allocation may result in high-priority messages being processed by inefficient nodes, while dynamic scheduling ensures that complex messages (such as dangerous goods return with a large number of attachments) are processed first by high-performance nodes, shortening the approval time. Attached Figure Description

[0019] This specification will be further described by way of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting; in these embodiments, the same reference numerals denote the same structures, wherein:

[0020] Figure 1 This is a flowchart illustrating an embodiment of the electronic seal and digital signature authentication method for paperless customs clearance in cross-border trade.

[0021] Figure 2 This is a schematic diagram of the structure of an export goods return and withdrawal application message shown in one embodiment of this application;

[0022] Figure 3 This is a schematic diagram of an export goods return application message shown in one embodiment of this application;

[0023] Figure 4 This is a schematic diagram of a data segment of the header of an application message for the return of exported goods to the warehouse, as shown in one embodiment of this application.

[0024] Figure 5 This is a schematic diagram of a data segment of the message body of an application message for the return of exported goods to the warehouse, as shown in one embodiment of this application;

[0025] Figure 6 This is a schematic diagram of a signed PDF file shown in one embodiment of this application;

[0026] Figure 7 This is a schematic diagram illustrating the signature certificate information of a signed PDF file in one embodiment of this application. Detailed Implementation

[0027] To more clearly illustrate the technical solutions of the embodiments in this specification, the accompanying drawings used in the description of the embodiments will be briefly introduced below.

[0028] Figure 1 This is a flowchart illustrating an embodiment of an electronic seal and digital signature authentication method for paperless customs clearance in cross-border trade. This method is an industrial data management method, such as... Figure 1 As shown, the electronic seal and digital signature authentication method for paperless customs clearance in cross-border trade may include the following steps.

[0029] S1. The cargo station system sends an application message for the return of exported goods to the air logistics platform.

[0030] A cargo terminal system is an information system used by air cargo terminals (i.e., airport cargo terminals or ground freight forwarding warehousing facilities) to manage the entire life cycle of goods, covering automated operations and data tracking of cargo receiving, storage, sorting, security inspection, loading, and return to the warehouse.

[0031] Core functions:

[0032] Cargo information management: Record basic cargo information (such as cargo number, weight, volume, product name, flight number, consignor and consignee, etc.).

[0033] Warehouse operations support: allocating storage locations, tracking cargo locations, and managing inventory status (such as awaiting shipment, inspected, or loaded).

[0034] Process automation: generating sorting instructions, printing labels, triggering security check processes, and coordinating loading plans.

[0035] Data interaction: It connects with airline systems, customs systems, air logistics platforms, etc., to synchronize cargo status in real time.

[0036] Application scenarios:

[0037] In the scenario of export goods being returned to the warehouse, the cargo station system needs to record the reason for the return (such as flight cancellation, customer order cancellation, goods damage, etc.), generate a return application, and trigger subsequent processes.

[0038] An air logistics platform is a digital collaborative platform that connects cargo terminals, airlines, customs, freight forwarders, shippers, and other parties. It provides full-chain visualization, automated operation, and resource integration services for goods, aiming to optimize air logistics efficiency, reduce costs, and improve user experience.

[0039] Core functions:

[0040] Data Hub:

[0041] Receive and parse messages sent from cargo terminal systems, airline systems, customs systems, etc. (such as return requests, flight status, customs clearance results).

[0042] Standardized data formats ensure cross-system compatibility.

[0043] Workflow collaboration:

[0044] Based on the return application message, subsequent operations are automatically triggered (such as notifying customs to release the goods, arranging return transportation, and updating the status of the goods).

[0045] Provide an exception handling mechanism (such as automatic retry or manual intervention when a withdrawal fails).

[0046] Visualization and Tracking:

[0047] Provide shippers and freight forwarders with real-time cargo status tracking (e.g., "returned from warehouse" or "in transit").

[0048] Generate reports (such as analysis of reasons for warehouse returns and cost statistics).

[0049] The export cargo return application message is a standardized data file sent electronically by the cargo terminal system or airport enterprise to the air logistics platform. It is used to apply for the return of export cargo that has been put into storage, security inspection, or flight allocation from the cargo terminal warehouse to the shipper, freight forwarder, or designated location, or to remove it from the current transportation plan.

[0050] Core function:

[0051] Triggering the return process: As an electronic application form, it replaces the traditional paper application form and initiates the return review, coordination and execution process.

[0052] Data sharing and collaboration: Real-time synchronization of information among cargo stations, customs, airlines, shippers, and other parties is achieved through structured data (such as cargo information, reasons for return, and operational instructions).

[0053] Achieve paperless operations: Businesses no longer need to print paper documents and travel back and forth to the freight station counter for stamps. The entire process of application, review, signing, and archiving can be completed online through the platform.

[0054] Figure 2 This is a schematic diagram of the structure of an export goods return / exit application message shown in one embodiment of this application, as follows: Figure 2 As shown, the export goods return application message includes a message header and a message body; the message header includes a unique message code, message function code, message type, sender code, receiver code, sending time, and message version number; the message body includes a unique business message number, file name, file extension, business type, and attachment data.

[0055] The specific content of the message header is shown in Table 1.

[0056] Table 1

[0057]

[0058] The specific content of the message body is shown in Table 2.

[0059] Table 2

[0060]

[0061]

[0062] In some embodiments, S1 specifically includes:

[0063] Obtain the historical message sending records of the cargo terminal system. The historical message sending records of the cargo terminal system can include multiple historical time periods and the total number of export cargo return and withdrawal application messages sent by the cargo terminal system.

[0064] Based on the historical message transmission records of the cargo station system, the export cargo return and withdrawal application messages are fragmented and encrypted;

[0065] Send the fragmented and encrypted export cargo return application message to the air logistics platform.

[0066] In some embodiments, based on the historical message transmission records of the cargo terminal system, the export cargo return and withdrawal application message is fragmented and encrypted, including:

[0067] Retrieve historical message transmission records from multiple other freight station systems;

[0068] Based on the historical message transmission records of the freight station system and the historical message transmission records of multiple other freight station systems, calculate the message correlation coefficient between the freight station system and other freight station systems;

[0069] Based on the message correlation coefficient between the freight station system and other freight station systems, identify other similar freight station systems;

[0070] Obtain message sending records of the freight station system at multiple time points in the current period (e.g., message volume per hour for the last 7 days) and message sending records of other similar freight station systems at multiple time points in the current period, and predict the message sending demand of the freight station system at multiple future time points in the current period.

[0071] Based on the message sending requirements of the cargo terminal system at multiple future time points in the current cycle, the export cargo return and withdrawal application messages are fragmented and encrypted.

[0072] Specifically, the total number of export cargo return and withdrawal application messages sent by the cargo terminal system in multiple historical time periods and the total number of export cargo return and withdrawal application messages sent by other cargo terminal systems in the same multiple historical time periods can be substituted into the correlation coefficient (e.g., Pearson correlation coefficient or Spearman rank correlation coefficient, etc.) calculation formula to calculate the message correlation coefficient between the cargo terminal system and other cargo terminal systems.

[0073] Other cargo terminal systems with a message correlation coefficient greater than the message correlation coefficient threshold (e.g., 0.5) can be considered as similar other cargo terminal systems.

[0074] Preferably, the message sending needs of the freight station system at multiple future time points in the current period can be predicted using a long short-term memory network model based on the message sending records of the freight station system at multiple time points in the current period (e.g., the message volume per hour in the last 7 days) and the message sending records of similar other freight station systems at multiple time points in the current period.

[0075] Specifically, long short-term memory network models can include:

[0076] 1. Input layer:

[0077] 1.1 Input of target freight station data

[0078] Shape: (time step, number of features) (e.g., 24×5).

[0079] Specific features:

[0080] Message volume: The total number of messages sent in the current hour (core target variable).

[0081] Time characteristics:

[0082] Hours (0-23, one-hot encoding or periodic encoding).

[0083] Day of the week (0-6, unique hot code).

[0084] Is it a holiday? (0 / 1)

[0085] Statistical characteristics:

[0086] The moving average of message volume over the past 3 hours (smoothing out short-term fluctuations).

[0087] The standard deviation of message volume over the past 24 hours (a measure of volatility).

[0088] 1.2 Input of similar freight station data

[0089] Shape: (time step, number of similar freight stations × number of features) (e.g., 24 × (3 freight stations × 2 features)).

[0090] Feature design:

[0091] Message volume: The total number of messages sent by each similar freight station in the current hour.

[0092] Collaborative features:

[0093] Message volume change rate (difference from the previous hour).

[0094] Correlation with message volume at the target cargo terminal.

[0095] Key points:

[0096] Similar freight stations must have similar business attributes to the target freight station (such as geographical location and cargo volume).

[0097] The list of similar freight stations is dynamically updated (e.g., recalculating relevance monthly).

[0098] 2. LSTM layer:

[0099] Target cargo station branch: 1-2 layers of LSTM (e.g., 64 units) to extract the time dependency pattern of the target cargo station itself (e.g., daily peak, weekly cycle).

[0100] Similar freight station branch: 1-layer LSTM (e.g., 32 cells) to capture the coordinated changes between similar freight stations and the target freight station (e.g., the impact of regional events).

[0101] 3. Blending Layer:

[0102] The outputs of the two branches are concatenated, merging the LSTM outputs of the target freight station and similar freight stations, retaining their respective features, and then non-linearly integrating the concatenated features through a fully connected (Dense) layer to learn the interaction relationships across freight stations.

[0103] 4. Output layer:

[0104] It can directly predict multiple future time points (e.g., 6 hours), with each time point corresponding to a neuron.

[0105] Understandably, by analyzing historical message transmission data from cargo terminal systems and similar cargo terminals in the industry, future message transmission demand can be predicted. Based on the prediction results, export cargo return and withdrawal application messages are dynamically fragmented and encrypted before being sent to the air logistics platform, avoiding network congestion or delays caused by excessive data transmission in a single instance. Encryption and fragmentation reduce the risk of data leakage and meet the compliance requirements of air logistics for sensitive information (such as cargo details and company information). Predicting future demand based on historical data and dynamically adjusting the fragmentation strategy avoids resource waste or insufficient processing capacity. Traditional single-cargo-terminal models rely solely on their own historical data and are susceptible to local fluctuations (such as sudden failures causing a surge in messages). By introducing data from similar cargo terminals, the model can capture common patterns of regional events (such as holiday logistics peaks and extreme weather), reducing the prediction error (MAPE) by 15%–25%.

[0106] In some embodiments, based on the message transmission requirements of the cargo terminal system at multiple future time points in the current cycle, the export cargo return and withdrawal application message is fragmented and encrypted, including:

[0107] Establish a multi-objective piecewise optimization function;

[0108] The optimal fragment size is generated based on the message sending requirements of the cargo terminal system at multiple future time points in the current cycle, the file size of the export cargo return and withdrawal application message, and the multi-objective fragmentation optimization function.

[0109] The export goods return and withdrawal application message is first fragmented according to the optimal fragment size, generating multiple first data fragments of the export goods return and withdrawal application message;

[0110] For each first data segment, the risk value of the first data segment is determined based on the variable fields included in the first data segment. Based on the risk value of the first data segment, it is determined whether to perform secondary fragmentation on the first data segment. If so, the first data segment is further fragmented based on the risk value of the first data segment to generate multiple second data segments corresponding to the first data segment.

[0111] Encrypt the application messages for the return of exported goods after they have been segmented.

[0112] For example, the multi-objective piecewise optimization function can be:

[0113] f=min(α×AvgDelay+β×SystemLoad-γ×SecurityScore)

[0114]

[0115] Where f is the multi-objective fragmentation optimization function value, AvgDelay is the transmission delay, SystemLoad is the system load, SecurityScore is the security score, α, β, and γ are weights, where α, β, and γ are greater than 0, and α + β + γ = 1 (e.g., α is 0.3, β is 0.3, and γ is 0.4), F is the total packet size, B is the available bandwidth, N(s) is the number of fragments, and T... enc For the encryption time of a single fragment, T head For network protocol header transmission time (e.g., TCP / IP header occupies 40 bytes → 0.03ms / fragment, N) parallel ε represents the number of parallel transmission channels (e.g., 4 channels), and ε and δ are empirical coefficients (e.g., ε = 0.02, δ = 0.01).

[0116] Smaller fragments allow for more parallel transmission and theoretically shorter transmission time. However, excessively small fragments increase encryption / decryption overhead and the proportion of network protocol headers, thus prolonging the overall latency. Too many fragments can cause congestion in the server processing queue. High-risk data requires finer-grained fragmentation to reduce the impact of leaks.

[0117] Security can be determined based on the average ratio of the size of the variable field in each shard to the size of the shard; the smaller the average ratio, the higher the security.

[0118] Variable fields are fields in the message structure whose content is not fixed and may contain sensitive information or change dynamically. For example, variable fields can be shown in Table 3.

[0119] Table 3

[0120] Field type Example content Identifiers Goods ID, Customer ID, Order Number Numerical Class Value of goods, insured amount State class Is it a dangerous good? Is it urgent? Description class Goods description and remarks

[0121] Based on historical data, a basic fragment size range can be determined. This range is then adjusted according to the message sending demands of the freight station system at multiple future time points within the current period, resulting in the current fragment size range. Understandably, the higher the message sending demands of the freight station system at multiple future time points within the current period, the larger the maximum value of the current fragment size range should be, to avoid excessive computational resource consumption for fragmentation. Multiple fragment sizes are sampled from the current range, and the multi-objective fragmentation optimization function value corresponding to these sampled fragment sizes is calculated. The sampled fragment size with the largest multi-objective fragmentation optimization function value is taken as the optimal fragment size.

[0122] For each first data segment, calculate the ratio of the variable fields included in the first data segment to the size of the first data segment. The smaller the ratio, the lower the risk value. If the risk value of the first data segment is greater than the risk value threshold (e.g., 0.5), then the first data segment is further fragmented, dividing it into two equal second data segments. This is just an example. Figure 4 This is a schematic diagram of a data segment of the header of an export goods return application message shown in one embodiment of this application. Figure 5 This is a schematic diagram of a data segment of the message body of an application message for the return of exported goods to the warehouse, as shown in one embodiment of this application.

[0123] The fragmented export cargo return and withdrawal application messages are encrypted using a symmetric encryption algorithm (such as AES-256).

[0124] S2. The air logistics platform sends the application message for the return of exported goods to the air transport intelligent system.

[0125] In some embodiments, the intelligent air transport system includes a computing power cluster, wherein the computing power cluster includes a computing power scheduling node and multiple message approval nodes. The computing power scheduling node is used to allocate message approval nodes for export goods return and withdrawal application messages, and the message approval nodes are used to approve export goods return and withdrawal application messages.

[0126] Specifically, computing power scheduling nodes:

[0127] Core function: As an "intelligent commander", it is responsible for dynamically allocating message approval tasks to the optimal approval node.

[0128] Key capabilities:

[0129] Global view: Real-time monitoring of the status (load, faults, processing capacity) of all message approval nodes.

[0130] Policy engine: Based on message characteristics and node status, execute scheduling algorithms (such as weighted round-robin, priority queue).

[0131] Fault tolerance mechanism: Supports automatic reassignment or task rollback when approval nodes fail.

[0132] Message approval node:

[0133] Core function: To approve the legality of message content and compliance with business rules.

[0134] Key capabilities:

[0135] Specialized processing: Different nodes can be configured with specific approval rules (such as high-risk messages requiring manual review).

[0136] Status reporting: Periodically report load and health status (such as CPU / memory utilization) to the scheduling node.

[0137] Isolation: The approval process is independent, avoiding single-point failures from affecting the overall process.

[0138] In some embodiments, the computing power scheduling node is a message allocation and approval node for export goods return and withdrawal application messages, including:

[0139] Based on the business type, sending time, and attachment data in the message header, determine the message characteristics of the export goods return and withdrawal application message. The message characteristics can be structured feature vectors (e.g., {Business type: Urgent, Risk level: High, Attachment size: 15MB}).

[0140] Obtain the status information of each message approval node, such as real-time load: the number of messages currently being processed, queue length; resource usage: CPU / memory utilization, remaining network bandwidth;

[0141] Based on the message characteristics of the export goods return application message and the status information of each message approval node, message approval nodes are assigned to the export goods return application message.

[0142] Specifically, the following process can be used to assign message approval nodes to application messages for the return of exported goods to the warehouse:

[0143] Specialty matching: Only nodes that support the message business type will be retained (e.g., emergency return messages require nodes to support emergency processing expertise);

[0144] Resource threshold check: Exclude nodes with CPU / memory utilization > 90% or remaining bandwidth < attachment transmission requirements.

[0145] Health status check: Exclude nodes marked as "faulty" or "offline";

[0146] Calculate a comprehensive score for each candidate node. The higher the score, the higher the priority. The lower the real-time load percentage of the node and the lower the average CPU / memory / bandwidth utilization, the higher the comprehensive score.

[0147] If the highest-scoring node is unique, it is directly assigned; if there are ties, a message approval node is randomly selected.

[0148] In some embodiments, the message approval node is used to approve export goods return and withdrawal application messages, including:

[0149] Determine the multiple pre-defined approval rules corresponding to the application messages for the return of exported goods to the warehouse;

[0150] Obtain historical approval data;

[0151] Based on historical approval data, determine the review order of multiple preset approval rules corresponding to the application message for the return of exported goods to the warehouse;

[0152] The application for the return of exported goods to the warehouse is reviewed and approved according to the review order of multiple preset approval rules corresponding to the application.

[0153] For example, the pre-defined approval rules corresponding to the application message for the return of exported goods to the warehouse may include:

[0154] Business compliance requirements: such as customs regulations ("Danger goods returned to the warehouse require an MSDS certificate") and airline operating procedures ("Overweight cargo returns require additional approval").

[0155] Risk control strategies include: "High-value goods returned to the warehouse require secondary manual review" and "Customer messages with historical violation records are automatically marked as high-risk".

[0156] System default rules include "header integrity check" and "attachment format verification (PDF / Excel)".

[0157] By combining the rule priority with the pass rate of the preset approval rules, a weighted scoring method is used to calculate the ranking weight of each rule. The higher the rule priority or the lower the pass rate, the earlier the preset approval rule will be reviewed.

[0158] The approval process for an application to return or withdraw goods from a warehouse can include the following steps, based on the review order of multiple pre-defined approval rules corresponding to the application:

[0159] S21. Initialization: Load the sorted list of rules and initialize the approval result to "Pending".

[0160] S22. Check item by item:

[0161] If the rule is approved, proceed to check the next rule;

[0162] If the rule is rejected, the approval process will be terminated immediately, and the reason for rejection will be returned.

[0163] If a rule triggers manual review (such as R003), automatic approval will be suspended and transferred to the manual channel.

[0164] S23. Results Summary: After all rules are approved, mark the message as "successfully entered into the database" and record the execution log of each rule.

[0165] In some embodiments, the message approval node is also used for:

[0166] Based on the review results of multiple pre-defined approval rules corresponding to the export goods return and withdrawal application, review personnel are assigned. For example, the personnel with the fewest uncompleted tasks may be assigned to the review. If multiple pre-defined approval rules result in failure, the review will be prioritized for personnel with higher skill levels or more work experience.

[0167] S3. The air logistics platform receives the receipt from the intelligent air transport system and puts it into storage.

[0168] S4. If the receipt indicates successful warehousing, the air logistics platform generates a PDF file based on the business message content and calls the signing server to sign the PDF file.

[0169] S5. The signing server uses the certificate hosted by the cargo station system to sign the PDF file and returns the signed PDF file to the air logistics platform.

[0170] S6. The air logistics platform will push the signed PDF file to the cargo station system.

[0171] Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments described herein. Other variations may also fall within the scope of this specification. Therefore, alternative configurations of the embodiments described herein are intended to be illustrative rather than limiting, and should be considered consistent with the teachings of this specification. Accordingly, the embodiments described herein are not limited to those explicitly introduced and described herein.

Claims

1. A method for electronic seals and digital signature authentication in paperless customs clearance for cross-border trade, characterized in that: include: The cargo terminal system sends an application message for the return of exported goods to the air logistics platform; The air logistics platform sends the application message for the return of exported goods to the air transport intelligent system; The air logistics platform receives receipts from the intelligent air freight system and stores them in the warehouse. If the receipt indicates successful warehousing, the air logistics platform generates a PDF file based on the business message content and calls the signing server to sign the PDF file; The signing server uses a certificate hosted by the cargo terminal system to sign the PDF file and returns the signed PDF file to the air logistics platform; The air logistics platform will push the signed PDF file to the cargo terminal system; The application message for the return of exported goods to the warehouse includes a message header and a message body; The message header includes a unique message code, a message function code, a message type, a sender code, a receiver code, a sending time, and a message version number; The message body includes a unique business message number, file name, file extension, business type, and attachment data; The cargo terminal system sends an application message for the return of exported goods to the air logistics platform, including: Retrieve historical message sending records from the freight station system; Based on the historical message transmission records of the cargo station system, the export cargo return and withdrawal application messages are fragmented and encrypted; Send the fragmented and encrypted export cargo return application message to the air logistics platform; Based on the historical message transmission records of the cargo terminal system, the export cargo return and withdrawal application messages are fragmented and encrypted, including: Retrieve historical message transmission records from multiple other freight station systems; Based on the historical message transmission records of the freight station system and the historical message transmission records of multiple other freight station systems, calculate the message correlation coefficient between the freight station system and other freight station systems; Based on the message correlation coefficient between the freight station system and other freight station systems, identify other similar freight station systems; Obtain message sending records of the freight station system at multiple time points in the current period and message sending records of other similar freight station systems at multiple time points in the current period, and predict the message sending needs of the freight station system at multiple future time points in the current period; Based on the message sending requirements of the cargo terminal system at multiple future time points in the current cycle, the export cargo return and withdrawal application messages are fragmented and encrypted.

2. The electronic seal and digital signature authentication method for paperless customs clearance in cross-border trade according to claim 1, characterized in that, The freight station system is also used for: Obtain the certificate information query request initiated by the user terminal corresponding to the application message for the return of exported goods to the warehouse; Based on the certificate information query request, the signature certificate information of the signed PDF file is displayed.

3. The electronic seal and digital signature authentication method for paperless customs clearance in cross-border trade according to claim 1, characterized in that, Based on the message sending requirements of the cargo terminal system at multiple future time points in the current cycle, the export cargo return and withdrawal application messages are fragmented and encrypted, including: Establish a multi-objective piecewise optimization function; The optimal fragment size is generated based on the message sending requirements of the cargo terminal system at multiple future time points in the current cycle, the file size of the export cargo return and withdrawal application message, and the multi-objective fragmentation optimization function. The export goods return and withdrawal application message is first fragmented according to the optimal fragment size, generating multiple first data fragments of the export goods return and withdrawal application message; For each first data segment, the risk value of the first data segment is determined based on the variable fields included in the first data segment. Based on the risk value of the first data segment, it is determined whether to perform secondary fragmentation on the first data segment. If so, the first data segment is further fragmented based on the risk value of the first data segment to generate multiple second data segments corresponding to the first data segment. Encrypt the application messages for the return of exported goods after they have been segmented.

4. The electronic seal and digital signature authentication method for paperless customs clearance in cross-border trade according to claim 3, characterized in that, The intelligent air transport system includes a computing power cluster, which includes a computing power scheduling node and multiple message approval nodes. The computing power scheduling node is used to allocate message approval nodes for export goods return applications, and the message approval nodes are used to approve export goods return applications.

5. The electronic seal and digital signature authentication method for paperless customs clearance in cross-border trade according to claim 4, characterized in that, The computing power scheduling node is a message allocation and approval node for export goods return and withdrawal application messages, including: Based on the business type, sending time, and attachment data in the message header, determine the message characteristics of the export goods return and withdrawal application message; Obtain the status information of each message approval node; Based on the message characteristics of the export goods return application message and the status information of each message approval node, message approval nodes are assigned to the export goods return application message.

6. The electronic seal and digital signature authentication method for paperless customs clearance in cross-border trade according to claim 4, characterized in that, The message approval node is used to approve export goods return and withdrawal application messages, including: Determine the multiple pre-defined approval rules corresponding to the application messages for the return of exported goods to the warehouse; Obtain historical approval data; Based on historical approval data, determine the review order of multiple preset approval rules corresponding to the application message for the return of exported goods to the warehouse; The application for the return of exported goods to the warehouse is reviewed and approved according to the review order of multiple preset approval rules corresponding to the application.

7. The electronic seal and digital signature authentication method for paperless customs clearance in cross-border trade according to claim 6, characterized in that, The message approval node is also used for: Based on the review results of the multiple preset approval rules corresponding to the application for return of exported goods to the warehouse, review personnel are assigned.

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