O2O cross-border transaction security authentication and risk control system and method for agricultural and sideline products facing "one belt and one road"
By constructing a closed-loop management system across the entire supply chain, the problems of data silos, low accuracy of risk assessment, insufficient security evidence storage, and poor compliance of contract execution in existing cross-border agricultural and sideline product trading systems have been solved, thereby improving the security, transparency, and trustworthiness of cross-border transactions.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- BEIJING SYBIS TECHNOLOGY CO LTD
- Filing Date
- 2026-04-27
- Publication Date
- 2026-07-24
AI Technical Summary
Existing cross-border trading systems for agricultural and sideline products suffer from problems in terms of security authentication and risk control, such as data silos, low accuracy of risk assessment, insufficient security evidence storage, poor contract execution compliance, inadequate payment risk control, incomplete identity authentication, poor anomaly detection, single early warning strategies, and long-term fixed risk control strategies. These issues make them unable to adapt to the differentiated requirements and dynamic changes of various countries.
It employs a cross-border transaction data collection module, a multi-source heterogeneous data fusion module, a dynamic risk scoring module, a blockchain secure evidence storage module, a smart contract execution module, a cross-border payment risk control interface, a user behavior analysis engine, a multi-dimensional identity authentication module, and a real-time early warning push module. Combined with an improved entropy weight method, multilingual semantic alignment, zero-knowledge proof, multi-country legal adaptation, two-factor authentication, and a long short-term memory network model, it forms a closed-loop management system across the entire chain.
It enables real-time collection and fusion of cross-border transaction data, accurate dynamic risk assessment, data security and privacy protection, legality and enforceability of contracts, payment security, identity reliability, sensitive detection of abnormal behavior, and adaptive optimization of risk control strategies, significantly improving the security, transparency and trustworthiness of transactions.
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Figure CN122453404A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of cross-border e-commerce and agricultural product circulation safety technology, specifically to a security certification and risk control system and method for O2O cross-border transactions of agricultural and sideline products oriented towards the "Belt and Road" initiative. Background Technology
[0002] With the deepening of the Belt and Road Initiative, trade in agricultural and sideline products among participating countries has become increasingly frequent, and the scale of cross-border transactions has continued to expand. However, traditional cross-border agricultural and sideline product trading models have many shortcomings, particularly in the lack of systematic and intelligent technical means for safety certification and risk control. Existing cross-border trading platforms mostly rely on single data sources and static risk assessment methods, which cannot effectively address issues such as differences in laws and regulations among multiple countries, data heterogeneity due to multiple languages and coding standards, cross-border payment fraud, opaque logistics information, and quality and safety risks.
[0003] At the data collection level, existing systems often rely on manual input or a single interface to obtain transaction information, making it difficult to achieve real-time collection and synchronization of data across the entire chain, resulting in delayed risk identification. Different countries have different agricultural and sideline product classification and coding systems, logistics node identification, and inspection and quarantine standards. Existing platforms lack efficient multi-source heterogeneous data fusion capabilities and cannot achieve cross-language and cross-protocol semantic alignment and unified mapping, resulting in severe data silos.
[0004] In terms of risk assessment, existing methods mostly employ fixed-weight risk scoring models, which cannot dynamically adjust the importance of indicators according to changes in the trading environment. This results in low risk identification accuracy and high false positive and false negative rates. Some platforms have attempted to introduce machine learning models, but the training data sources are limited, the models have poor adaptability, and they struggle to cope with the complex trading scenarios in countries along the Belt and Road Initiative.
[0005] Regarding secure data storage, existing cross-border transaction systems mostly use centralized databases to store transaction records, which poses risks of data tampering and single points of failure. Although some platforms have introduced blockchain technology, most simply record transaction hashes on the chain without combining them with privacy protection technologies such as zero-knowledge proofs, making it difficult to balance data security and compliance requirements.
[0006] In terms of transaction execution, existing smart contracts have limited functionality and lack the ability to adapt to the laws and regulations of multiple countries. Compliance conflicts can easily arise during contract execution, leading to transaction failures or legal risks. Furthermore, cross-border payments often rely on a single payment channel, lacking multi-factor verification and real-time interception mechanisms, resulting in a high risk of payment fraud.
[0007] In terms of user identity verification, existing platforms mostly use single digital certificates or password verification, which cannot meet the diverse identity authentication needs of countries along the Belt and Road. Especially in cross-border scenarios, multi-factor authentication methods such as biometrics and local identity codes have not been effectively integrated, leading to an increase in the risk of identity forgery.
[0008] In terms of abnormal behavior detection, existing systems mostly rely on rule matching or simple statistical analysis, which cannot capture complex time-series abnormal patterns. This is especially true in the agricultural and sideline products sector, where transaction behavior is greatly affected by seasonal and policy factors, resulting in poor detection performance.
[0009] Regarding early warning push notifications, existing platforms mostly use uniform templates for early warning, lacking tiered response strategies for different risk levels. Regulatory agencies, trading parties, and logistics service providers cannot obtain differentiated and timely information, affecting the efficiency of risk handling.
[0010] In terms of strategy optimization, the existing system lacks an adaptive risk control strategy adjustment mechanism. The weights and thresholds are fixed in the long term, and cannot be dynamically optimized according to historical transaction data and changes in risk distribution, resulting in a decline in the effectiveness of the risk control system after long-term operation.
[0011] In summary, existing technologies for security certification and risk control in cross-border transactions of agricultural and sideline products have significant shortcomings in areas such as data fusion, risk assessment, secure evidence storage, smart contract compliance, payment risk control, identity authentication, anomaly detection, tiered early warning, and strategy optimization. There is an urgent need for a comprehensive system and method that can cover the entire chain, support the differentiated requirements of multiple countries, and has dynamic learning and adaptive capabilities. Summary of the Invention
[0012] The purpose of this invention is to provide a security authentication and risk control system and method for O2O cross-border transactions of agricultural and sideline products oriented towards the "Belt and Road" initiative.
[0013] To achieve the above objectives, this invention provides the following technical solution: a security authentication and risk control system and method for O2O cross-border transactions of agricultural and sideline products under the "Belt and Road" initiative, comprising a cross-border transaction data collection module. This module can collect real-time data on the identity information of buyers and sellers, transaction amount, transaction time, commodity type, quantity, price, logistics node status, inspection and quarantine results, and payment details throughout the entire process of transaction initiation, payment, logistics, quality inspection, and customs clearance, and marks these multi-type data with a unified timestamp; a multi-source heterogeneous data fusion module, used to standardize, map, and semantically align cross-border data from different countries, agreements, languages, and encoding formats, ensuring that various types of data can be correlated within the same analytical framework; and a dynamic risk scoring module, used to construct a multi-dimensional risk indicator set based on transaction amount, transaction frequency, historical credit records, logistics anomaly rate, and quality inspection pass rate, and calculate the dynamic risk score using the following formula. :
[0014] in For the first The weight of each indicator This is the standardized function of the indicator. The system comprises the following components: the original value of the indicator, with weights dynamically determined by an improved entropy weight method; a blockchain security storage module for writing key transaction data into the consortium blockchain after hash processing, supporting zero-knowledge proof verification to ensure data immutability and privacy verification; a smart contract execution module for automatically triggering payment settlement, logistics instructions, or risk disposal processes when preset conditions are met, and verifying compliance with laws in multiple countries before execution; a cross-border payment risk control interface for connecting to payment gateways in multiple countries and implementing real-time transaction interception and secondary verification; a user behavior analysis engine for identifying abnormal transaction patterns based on a time-series model; a multi-dimensional identity authentication module for comprehensive authentication by integrating biometrics, digital certificates, and local identity verification systems in Belt and Road countries; a real-time early warning push module for pushing high-risk transaction information to regulators and both parties to the transaction; and a strategy adaptive optimization module for dynamically adjusting the weights and thresholds of each indicator based on the risk score distribution, enabling continuous evolution of risk control strategies. The system covers the entire chain of data collection and processing for cross-border agricultural and sideline product transactions, achieving real-time data consistency in a multi-country, multi-protocol environment, avoiding information silos. Dynamic risk scoring combined with an improved entropy weight method makes risk assessment more accurate and adaptable to environmental changes. The combination of blockchain and zero-knowledge proofs protects privacy while ensuring data immutability. Smart contracts automatically execute transactions under legal compliance, improving efficiency and reducing the risk of human intervention. Multi-factor authentication and tiered early warning further enhance security and response speed, while adaptive strategy optimization ensures the long-term effectiveness of the system.
[0015] Furthermore, the multi-source heterogeneous data fusion module employs a multilingual semantic alignment method based on ontology mapping to convert the classification codes of agricultural and sideline products from different countries into a unified international coding standard, and establishes a cross-lingual attribute mapping table with the following mapping function:
[0016] in For local encoding, To ensure internationally standardized encoding, word vector similarity constraints are introduced into the mapping process:
[0017] when The system determines data to be mappable, thus achieving precise correspondence between different languages and encoding systems and ensuring consistency in subsequent analysis and evidence preservation. Through ontology mapping and word vector similarity constraints, it achieves accurate conversion between encoding systems from different countries, resolving the issue of semantic inconsistency in cross-border data. This provides a reliable data foundation for subsequent risk assessment, blockchain evidence preservation, and smart contract execution, avoiding misjudgments or data loss due to encoding differences.
[0018] Furthermore, the weights wi in the dynamic risk scoring module are determined by the improved entropy weight method, with the specific formula as follows:
[0019] in , For the sample size, This method uses a set of indicators to automatically adjust their importance based on changes in sample data, making risk assessment more aligned with the actual trading environment. The improved entropy weight method makes the weights dynamically adaptable, automatically optimizing them based on changes in historical trading data. This avoids assessment biases caused by fixed weights, thereby improving the accuracy of risk scoring and the system's intelligence level.
[0020] Furthermore, the blockchain security evidence storage module adopts a layered storage structure, storing transaction metadata on the chain, storing large-capacity original files on a distributed file system, and saving the file's hash value and access permission policy on the chain. The verification formula is as follows:
[0021] This architecture optimizes storage efficiency while ensuring data immutability and supports access control. Tiered storage balances security and storage costs, hash verification ensures data integrity, and access control policies guarantee controllable data access, making it particularly suitable for the evidence storage needs of massive amounts of data in cross-border transactions.
[0022] Furthermore, the smart contract execution module incorporates a multi-country legal adaptation rule base to perform compliance verification before contract execution. The verification function is as follows:
[0023] in For the contract content, This refers to a set of laws and regulations for the target country; execution is only possible if all rules are matched. The advantage of this claim is that it ensures the compliance of smart contracts under different national legal environments, avoiding transaction failures or legal risks due to legal conflicts, and improving the legality and enforceability of cross-border transactions.
[0024] Furthermore, the cross-border payment risk control interface adopts a protection mechanism combining two-factor dynamic verification codes and time window restrictions. The conditions under which transactions are allowed are as follows:
[0025] in Minimum transaction interval, This mechanism generates a time-sensitive verification code for the server. It effectively prevents payment fraud and duplicate transaction attacks. The combination of dynamic verification codes and time window restrictions enhances the security of the payment process, making it particularly suitable for multi-country payment gateway environments.
[0026] Furthermore, the user behavior analysis engine employs an anomaly detection model based on a Long Short-Term Memory (LSTM) network, and its prediction error formula is as follows:
[0027] when The behavior was deemed abnormal, among which For actual behavior vectors, The value is the model prediction, and τ is the dynamic threshold. The LSTM model can capture temporal anomaly patterns, and the dynamic threshold improves the sensitivity and accuracy of detection, making it particularly suitable for scenarios where agricultural and sideline product transactions are affected by seasons and policies.
[0028] Furthermore, the multi-dimensional identity authentication module integrates three types of authentication factors: biometrics. Digital Certificates Local ID Code The formula for its comprehensive certification score is:
[0029] in , , These are the matching scores for each factor. Multi-factor authentication enhances the reliability of identity verification, adapts to the diverse identity systems of countries along the Belt and Road Initiative, and effectively prevents the risk of identity forgery.
[0030] Furthermore, the real-time early warning push module adopts a risk-level-based tiered push strategy, with the risk level classification formula as follows:
[0031] Different risk levels correspond to different target audiences and response timeframes. This tiered push strategy improves the targeting and efficiency of risk management, avoids excessive interference with low-risk transactions, and ensures that high-risk transactions are processed promptly.
[0032] Furthermore, the process includes the following steps: Step 1: Acquire end-to-end data through the cross-border transaction data acquisition module; Step 2: Complete data standardization and semantic mapping using the multi-source heterogeneous data fusion module; Step 3: Calculate dynamic risk scores based on the improved entropy weight method. Step 4: Hash key data and write it to the blockchain for zero-knowledge verification; Step 5: Call the smart contract execution module for compliance verification and automatic execution; Step 6: Implement dual verification and transaction interception through the cross-border payment risk control interface; Step 7: Detect abnormal patterns using a user behavior analysis engine; Step 8: Complete third-party authentication and calculate a comprehensive score through a multi-dimensional identity authentication module; Step 9: Push early warning information based on risk level; Step 10: The strategy adaptive optimization module adjusts weights and thresholds based on historical score distribution to achieve continuous evolution of risk control strategies. Advantages: This method forms a closed-loop management system covering the entire transaction lifecycle, with each link closely connected. It can achieve safe, compliant, and efficient cross-border transactions in complex multi-country environments, significantly improving overall risk control level and transaction trust.
[0033] This invention provides a security authentication and risk control system and method for O2O cross-border transactions of agricultural and sideline products oriented towards the "Belt and Road" initiative, which has the following beneficial effects: This invention significantly enhances the security and risk control capabilities of O2O cross-border transactions of agricultural and sideline products oriented towards the "Belt and Road" initiative. Its advantages stem from the novel system architecture and methodological process defined in the claims, specifically in the following aspects.
[0034] First, the system achieves real-time data collection across the entire data chain, covering information on buyers and sellers, logistics nodes, inspection and quarantine information, and payment records, ensuring timely and comprehensive risk identification. The multi-source heterogeneous data fusion module uses an ontology-based multilingual semantic alignment method to convert the classification codes of agricultural and sideline products from different countries into a unified international coding standard. It also establishes a cross-linguistic attribute mapping table and uses word vector similarity constraints to ensure the accuracy of the mapping, thereby breaking down data silos and achieving seamless integration and correlation analysis of cross-border data.
[0035] Secondly, the dynamic risk scoring module uses an improved entropy weight method to determine indicator weights, which can automatically adjust the importance of each indicator according to changes in sample data. Combined with a standardized function, it calculates a dynamic risk score, making risk assessment more accurate. This model overcomes the limitations of traditional fixed-weight methods, adapts to the different trading environments and risk characteristics of countries along the Belt and Road Initiative, and significantly reduces false positives and false negatives.
[0036] Third, the blockchain secure evidence storage module adopts a layered storage structure, storing transaction metadata on the chain and large-capacity original files on a distributed file system. File hash values and access permission policies are also stored on the chain, combined with zero-knowledge proof technology to achieve privacy protection and tamper-proof authentication. This design ensures both data security and integrity while meeting compliance requirements for data privacy in cross-border transactions.
[0037] Fourth, the smart contract execution module incorporates a multi-country legal adaptation rule library, performing compliance checks before contract execution to ensure that the transaction content complies with the laws and regulations of the target country, avoiding transaction failures or risks due to legal conflicts. This mechanism significantly enhances the legality and enforceability of cross-border transactions.
[0038] Fifth, the cross-border payment risk control interface employs a protection mechanism combining two-factor dynamic verification codes and time window restrictions, effectively preventing payment fraud and duplicate transaction attacks, and ensuring fund security. This mechanism operates stably in multi-country payment gateway environments, enhancing the reliability of the payment process.
[0039] Sixth, the user behavior analysis engine builds an anomaly detection model based on a long short-term memory network, which can capture complex temporal anomaly patterns, making it particularly suitable for scenarios where agricultural and sideline product transactions are affected by seasonal and policy factors. This model improves the sensitivity and accuracy of anomaly detection by judging abnormal behavior through prediction errors and dynamic thresholds.
[0040] Seventh, the multi-dimensional identity authentication module integrates three authentication factors: biometrics, digital certificates, and local identity codes, and calculates a comprehensive authentication score to ensure the authenticity of the user's identity. This design can meet the diverse identity authentication needs of countries along the Belt and Road Initiative and effectively prevent the risk of identity forgery.
[0041] Eighth, the real-time early warning push module uses a risk-level tiered push strategy to push early warning information to the corresponding regulators and trading entities according to different risk levels, and sets different response time limits to ensure that high-risk transactions can be processed in a timely manner and low-risk transactions can avoid excessive interference, thereby improving the efficiency and pertinence of risk management.
[0042] Ninth, the strategy adaptive optimization module can dynamically adjust the weights and thresholds of each indicator based on the historical risk score distribution, enabling the continuous evolution of risk control strategies. This mechanism allows the system to continuously optimize performance over long-term operation, adapt to changes in the trading environment and risk characteristics, and maintain a high level of risk control capabilities.
[0043] Tenth, the overall methodology achieves closed-loop management across the entire transaction lifecycle, from data collection and integration, risk assessment, secure storage, smart contract execution, payment risk control, behavioral analysis, identity authentication, tiered early warning, to strategy optimization. This forms a comprehensive security authentication and risk control system covering the entire transaction lifecycle. This system not only solves problems such as data silos, low risk assessment accuracy, insufficient security, and lack of compliance in existing technologies, but also possesses excellent scalability and adaptability. It can operate stably in the diverse trading environments of countries along the Belt and Road Initiative, significantly improving the security, transparency, and trustworthiness of cross-border agricultural and sideline product transactions. Attached Figure Description
[0044] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are merely exemplary, and those skilled in the art can derive other embodiments based on the provided drawings without creative effort.
[0045] Figure 1 This is a diagram illustrating the overall operational logic of the system of this invention. Figure 2 This is a flowchart of the data acquisition and fusion process of the present invention; Figure 3 This is a flowchart of the risk assessment and evidence preservation process for this invention. Detailed Implementation
[0046] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses consistent with some aspects of this disclosure as detailed in the appended claims.
[0047] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.
[0048] How to use: Use of the cross-border transaction data collection module: When a cross-border transaction of agricultural and sideline products is initiated, the cross-border transaction data collection module is activated to obtain in real time the identity information of the buyer and seller, transaction amount, transaction time, commodity type, quantity, price, logistics node status, inspection and quarantine results, and payment details. Each piece of data is stamped with a unified timestamp to ensure that the data across the entire chain remains consistent in the time dimension, providing a complete data source for subsequent integration and risk assessment.
[0049] Use of the multi-source heterogeneous data fusion module: After data acquisition, the multi-source heterogeneous data fusion module is activated to standardize and transform cross-border data from different countries, protocols, languages, and encoding formats. It calls a multilingual semantic alignment method based on ontology mapping to convert local agricultural product classification codes into internationally unified codes, and uses word vector similarity constraints for mapping determination, ensuring that data from different sources are completely semantically and analytically aligned, thus eliminating data silos.
[0050] The dynamic risk scoring module is used as follows: After data integration, the system inputs the data into the dynamic risk scoring module. Based on transaction amount, transaction frequency, historical credit records, logistics anomaly rate, and quality inspection pass rate, the system constructs a multi-dimensional risk indicator set. It then uses an improved entropy weight method to calculate the weights of each indicator and processes the original indicator values using a standardized function, following the formula...
[0051] Calculate a dynamic risk score so that the assessment results can reflect the true risk level of the current trading environment.
[0052] The blockchain secure evidence storage module is used as follows: Key transaction data is hashed to obtain hash values. The blockchain secure evidence storage module then writes these hash values to the consortium blockchain, simultaneously storing access control policies on the chain. If data integrity verification is required, the file hash is recalculated and applied according to the formula.
[0053] The comparison is performed, and zero-knowledge proof technology is used to achieve privacy protection and tamper-proof authentication.
[0054] Using the smart contract execution module: When a transaction enters the execution phase, the smart contract execution module is invoked. The system first reads the built-in multi-country legal adaptation rule library to perform compliance verification on the contract content. The verification formula is as follows:
[0055] The contract will only automatically trigger payment settlement, logistics instructions, or risk management processes when all rules are matched, ensuring that the transaction is legal and executable.
[0056] Use of the cross-border payment risk control interface: During the payment process, the cross-border payment risk control interface is enabled. The system obtains the current time and the time of the last transaction to determine whether the time window restriction conditions are met.
[0057] And verify whether the dynamic verification code entered by the user matches the verification code generated by the server, that is
[0058] Payment can only be completed after two-factor authentication is successful; otherwise, the transaction will be blocked and a risk warning will be displayed.
[0059] During the transaction process, user behavior data is continuously input into the user behavior analysis engine, which calculates the prediction error based on a long short-term memory network model.
[0060] When the error exceeds the dynamic threshold, it is judged as abnormal behavior, and the corresponding monitoring and early warning process is triggered.
[0061] The multi-dimensional identity authentication module is used during user login and transaction confirmation. It integrates three authentication factors: biometrics, digital certificates, and local identity codes, to calculate a comprehensive authentication score.
[0062] The scores of the three factors are weighted and summed, and only when the overall score reaches the set standard is the certification considered passed.
[0063] Using the real-time early warning push module: Based on the dynamic risk scoring results, the real-time early warning push module is invoked, and the system classifies risks according to the risk level formula.
[0064] Early warning information is pushed to the relevant regulators and trading entities, with different response time limits set for different levels to ensure that high-risk transactions are prioritized.
[0065] Use of the adaptive strategy optimization module: After the system has been running for a period of time, the adaptive strategy optimization module is called to recalculate the weights and thresholds of each indicator based on the historical risk score distribution, and update the parameters of the dynamic risk score model, so that the risk control strategy can be continuously optimized as the trading environment and risk characteristics change, and the system can maintain long-term effective operation.
[0066] Example: Example 1 In cross-border agricultural and sideline product transactions, the trading parties are located in different countries along the Belt and Road Initiative. After system startup, the cross-border transaction data acquisition module first acquires real-time information on the identity of the buyer and seller, product type, quantity, price, logistics node status, inspection and quarantine results, and payment details during the transaction initiation phase. All data is timestamped to ensure consistency across the entire data chain. Subsequently, the multi-source heterogeneous data fusion module standardizes data from different protocols, languages, and encoding systems. Using an ontology-based multilingual semantic alignment method, local classification codes are mapped to internationally unified codes, and word vector similarity constraints are used to determine the mapping relationship, achieving cross-language and cross-encoding semantic alignment. The fused data then enters the dynamic risk scoring module. The system constructs a multi-dimensional risk indicator set based on transaction amount, transaction frequency, historical credit records, logistics anomaly rate, and quality inspection pass rate. An improved entropy weight method is used to calculate the weight of each indicator, and a dynamic risk score is derived by combining it with a standardized function, enabling a quantitative assessment of the current transaction risk. Key transaction data, after hash processing, is written to the consortium blockchain by the blockchain security storage module, which also stores access control policies. Zero-knowledge proof technology is used to achieve privacy protection and tamper-proof authentication. Before contract execution, the smart contract execution module calls a multi-country legal adaptation rule base for compliance verification, ensuring the contract content complies with the laws and regulations of the target country. Upon successful verification, payment settlement, logistics instructions, or risk handling processes are automatically triggered. The payment process utilizes a cross-border payment risk control interface to implement two-factor dynamic verification codes and time window restrictions to ensure transaction security. The user behavior analysis engine continuously monitors transaction behavior based on a long short-term memory network model, calculates prediction errors, and triggers alerts when anomalies occur. The multi-dimensional identity authentication module integrates biometrics, digital certificates, and local identity codes to calculate a comprehensive authentication score; only transactions that pass authentication can continue. The real-time alert push module classifies risk levels based on risk scores and pushes alert information to the corresponding regulators and transaction entities. The strategy adaptive optimization module dynamically adjusts indicator weights and thresholds based on historical score distribution, continuously optimizing the risk control strategy.
[0067] Example 2
[0068] In O2O cross-border transactions of agricultural and sideline products in countries along the Belt and Road Initiative, buyers and sellers reach transaction intentions through online platforms. The cross-border transaction data collection module continuously collects information on logistics node changes, inspection and quarantine results updates, and payment transaction details throughout the entire transaction process, maintaining timestamp synchronization. The multi-source heterogeneous data fusion module identifies differences in data protocols across countries, uses ontology mapping to convert local agricultural and sideline product classification codes into internationally unified codes, and ensures accurate mapping through word vector similarity constraints. The dynamic risk scoring module receives the fused data, constructs a multi-dimensional indicator set including transaction amount, transaction frequency, historical credit, logistics anomaly rate, and quality inspection pass rate, calculates weights using an improved entropy weight method, and derives a dynamic risk score using a standardized function, achieving risk quantification. The blockchain secure evidence storage module hashes key transaction data and writes it to the consortium blockchain, attaching access permission policies and using zero-knowledge proofs to achieve privacy protection and tamper-proofing. The smart contract execution module calls a multi-country legal adaptation rule base for compliance verification before contract execution, ensuring the contract complies with the laws of the target country; after successful verification, the transaction is automatically executed. The cross-border payment risk control interface employs two-factor authentication to prevent fraud by limiting the verification time window and using dynamic verification codes during the payment process. The user behavior analysis engine utilizes a long short-term memory network model to analyze transaction time-series characteristics, calculate prediction errors, and issue alerts when anomalies occur. The multi-dimensional identity authentication module integrates biometrics, digital certificates, and local identity codes to calculate a comprehensive authentication score, ensuring the authenticity of the transaction entity. The real-time early warning push module categorizes risks based on their scores and pushes warning information. The strategy adaptive optimization module adjusts weights and thresholds based on historical score distribution, enabling continuous evolution of the risk control strategy.
[0069] Example 3
[0070] In cross-border agricultural and sideline product transactions with countries along the Belt and Road Initiative, the system is applied to end-to-end risk control under the O2O model. The cross-border transaction data collection module collects and timestamps data in real time at each stage of transaction initiation, payment, logistics, quality inspection, and customs clearance. The multi-source heterogeneous data fusion module standardizes and converts data from different languages, encodings, and protocols, using ontology mapping and word vector similarity constraints to achieve accurate mapping from local encoding to internationally unified encoding. The dynamic risk scoring module constructs a multi-dimensional indicator set based on transaction amount, transaction frequency, historical credit, logistics anomaly rate, and quality inspection pass rate, calculates weights using an improved entropy weight method, and derives a dynamic risk score through a standardized function. The blockchain secure evidence storage module hashes key transaction data and writes it to the consortium blockchain, storing access permission policies and combining zero-knowledge proofs to achieve privacy protection and tamper-proofing. The smart contract execution module calls a multi-country legal adaptation rule base for compliance verification before contract execution, automatically executing payment settlement, logistics instructions, or risk disposal after ensuring the contract's legality. The cross-border payment risk control interface verifies time window limits and dynamic verification codes during the payment process, using two-factor authentication to ensure transaction security. The user behavior analysis engine calculates prediction errors based on a long short-term memory network model and triggers alerts when anomalies occur. The multi-dimensional identity authentication module integrates biometrics, digital certificates, and local identity codes to calculate a comprehensive authentication score, ensuring identity authenticity. The real-time alert push module categorizes risks based on their scores and pushes alert information. The strategy adaptive optimization module adjusts weights and thresholds based on historical score distributions to continuously optimize risk control strategies.
[0071] Example 4
[0072] In cross-border O2O transactions of agricultural and sideline products in countries along the Belt and Road Initiative, the system is used for the identification and handling of high-risk transactions. The cross-border transaction data acquisition module acquires data from the entire chain in real time and maintains consistent timestamps. The multi-source heterogeneous data fusion module converts local encoding to internationally unified encoding through ontology mapping and word vector similarity constraints. The dynamic risk scoring module constructs a multi-dimensional indicator set, calculates weights using an improved entropy weight method, and derives a dynamic risk score. The blockchain secure evidence storage module hashes key data and writes it to the consortium blockchain, attaching access permission policies and using zero-knowledge proofs to achieve privacy protection and tamper-proofing. The smart contract execution module calls a multi-country legal adaptation rule base for compliance verification before contract execution, ensuring the contract is legal before automatic execution. The cross-border payment risk control interface verifies time window limits and dynamic verification codes during the payment process, using two-factor authentication to prevent fraud. The user behavior analysis engine calculates prediction errors based on a long short-term memory network model and triggers warnings when anomalies occur. The multi-dimensional identity authentication module integrates biometrics, digital certificates, and local identity codes to calculate a comprehensive authentication score, ensuring identity authenticity. The real-time warning push module classifies risks based on risk scores and pushes warning information. The strategy adaptive optimization module adjusts weights and thresholds based on historical score distribution to achieve continuous evolution of risk control strategies.
[0073] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.
Claims
1. A security authentication and risk control system and method for O2O cross-border transactions of agricultural and sideline products oriented towards the "Belt and Road" initiative, characterized in that, include: The cross-border transaction data collection module is used to collect transaction information, logistics node information, inspection and quarantine information, and payment flow information from both buyers and sellers in real time. The multi-source heterogeneous data fusion module is used to standardize and map cross-border data with different protocols, languages, and encoding formats. The dynamic risk scoring module is used to construct a multi-dimensional risk indicator set based on transaction amount, transaction frequency, historical credit, logistics anomaly rate, and quality inspection pass rate, and calculates the dynamic risk score using the following formula. : in, For the first The weight of each indicator This is the standardized function of the indicator. This is the original value of the indicator; The blockchain security storage module is used to write key transaction data into the consortium blockchain after hash processing, and supports zero-knowledge proof verification. The smart contract execution module is used to automatically trigger payment settlement, logistics instructions or risk disposal processes when preset conditions are met. Cross-border payment risk control interface, used to connect to payment gateways in multiple countries and implement real-time transaction interception and secondary verification; A user behavior analysis engine is used to identify abnormal transaction patterns based on a time-series model. The multi-dimensional identity authentication module is used to integrate biometrics, digital certificates, and local identity verification systems in countries along the Belt and Road Initiative. The real-time early warning push module is used to push high-risk transaction information to regulators and both parties to the transaction; The strategy adaptive optimization module is used to dynamically adjust the weights and thresholds of each indicator based on the risk score distribution.
2. The security authentication and risk control system and method for O2O cross-border transactions of agricultural and sideline products oriented towards the "Belt and Road" initiative, as described in claim 1, is characterized in that... The multi-source heterogeneous data fusion module employs a multilingual semantic alignment method based on ontology mapping to convert the classification codes of agricultural and sideline products from different countries into a unified international coding standard, and establishes a cross-lingual attribute mapping table with the following mapping function: in For local encoding, To ensure internationally standardized encoding, word vector similarity constraints are introduced into the mapping process: when It is determined to be mappable at that time.
3. The security authentication and risk control system and method for O2O cross-border transactions of agricultural and sideline products oriented towards the "Belt and Road" initiative, as described in claim 1, is characterized in that... The weight wi in the dynamic risk scoring module is determined by the improved entropy weight method, and the specific formula is as follows: in , For the sample size, For the number of indicators.
4. The security authentication and risk control system and method for O2O cross-border transactions of agricultural and sideline products oriented towards the "Belt and Road" initiative, as described in claim 1, is characterized in that... The blockchain security evidence storage module adopts a layered storage structure, storing transaction metadata on the chain, storing large-capacity original files on a distributed file system, and saving the file's hash value and access permission policy on the chain. The verification formula is as follows: 。 5. The security authentication and risk control system and method for O2O cross-border transactions of agricultural and sideline products oriented towards the "Belt and Road" initiative, as described in claim 1, is characterized in that... The smart contract execution module has a built-in rule library adapted to the laws of multiple countries. Before contract execution, a compliance check is performed. The check function is: in For the contract content, A set of laws and regulations for the target country.
6. The security authentication and risk control system and method for O2O cross-border transactions of agricultural and sideline products oriented towards the "Belt and Road" initiative, as described in claim 1, is characterized in that... The cross-border payment risk control interface adopts a protection mechanism combining two-factor dynamic verification codes and time window restrictions. The conditions under which transactions are allowed are as follows: in Minimum transaction interval, A time-sensitive verification code generated for the server.
7. The security authentication and risk control system and method for O2O cross-border transactions of agricultural and sideline products oriented towards the "Belt and Road" initiative, as described in claim 1, is characterized in that... The user behavior analysis engine employs an anomaly detection model based on Long Short-Term Memory (LSTM) networks, and its prediction error formula is as follows: when This is considered abnormal behavior, among which For actual behavior vectors, These are the model's predicted values. This is a dynamic threshold.
8. A security authentication and risk control system and method for O2O cross-border transactions of agricultural and sideline products oriented towards the "Belt and Road" initiative, as described in claim 1, is characterized in that... The multidimensional identity authentication module integrates three types of authentication factors: biometrics. Digital Certificates Local ID Code The formula for its comprehensive certification score is: in , , These are the matching scores for each factor. .
9. A security authentication and risk control system and method for O2O cross-border transactions of agricultural and sideline products oriented towards the "Belt and Road" initiative, as described in claim 1, is characterized in that... The real-time early warning push module adopts a risk-level-based hierarchical push strategy, and the risk level classification formula is as follows: Different levels correspond to different push targets and response time limits.
10. A security authentication and risk control system and method for O2O cross-border transactions of agricultural and sideline products oriented towards the "Belt and Road" initiative, as described in claim 1, is characterized in that... Includes the following steps: Step 1: Obtain end-to-end data through the cross-border transaction data collection module; Step 2: Use the multi-source heterogeneous data fusion module to complete data standardization and semantic mapping; Step 3: Calculate dynamic risk score based on improved entropy weight method ; Step 4: Hash the key data, write it into the blockchain, and perform zero-knowledge verification; Step 5: Call the smart contract execution module to perform compliance verification and automatic execution; Step 6: Implement dual verification and transaction interception through the cross-border payment risk control interface; Step 7: Detect abnormal patterns using a user behavior analysis engine; Step 8: Complete third-party authentication and calculate the overall score through the multi-dimensional identity authentication module; Step 9: Push early warning information based on the risk level; Step 10: The strategy adaptive optimization module adjusts the weights and thresholds based on the historical score distribution to achieve continuous evolution of the risk control strategy.