Payment routing method and device based on voiceprint encryption, equipment and medium

Abstract

The invention discloses a payment routing method and device based on voiceprint encryption, equipment and a medium, and the method comprises the steps: obtaining a plurality of voiceprint secret key fragments containing voiceprint features and payment information based on a voice payment instruction of a user, and obtaining a plurality of static secret key fragments used for access authorization; performing routing evaluation on a plurality of preset cross-border payment paths to obtain a target path for payment settlement; performing encryption processing on each voiceprint key fragment to obtain a plurality of anonymous identifiers matched with the target path; performing combined verification on each voiceprint key fragment and each static key fragment according to each anonymous identifier to obtain a routing verification result; and sending the route verification result and each anonymous identifier to the target path for payment settlement. According to the method, payment authentication security is enhanced through a dual verification mechanism of voiceprint key fragmentation and static key fragmentation, and the method is suitable for a high-sensitivity financial scene and can assist a financial institution to quickly access a mainstream cross-border payment network.

Description

Technical Field

[0001] This invention relates to the field of cross-border payments, and in particular to a payment routing method, apparatus, device, and medium based on voiceprint encryption. Background Technology

[0002] With the continuous growth of global cross-border transactions, traditional payment systems have exposed problems such as strong path dependence, low response efficiency, and weak security mechanisms when handling multi-currency settlements and inter-institutional clearing. Especially in high-concurrency transaction scenarios, centralized architectures are prone to system latency and single-point-of-failure risks, making it difficult to meet the dual requirements of real-time performance and stability. At the same time, user authentication methods are vulnerable to illegal acquisition or impersonation. Payment routing technology, as a core component of cross-border payments, directly impacts transaction experience and fund security through its security and efficiency. Existing payment routing primarily relies on manual settings or static allocation of payment paths based on historical transaction data, resulting in delayed routing decisions and insufficient adaptability and security, making it difficult to cope with the complex and ever-changing international payment network environment. Summary of the Invention

[0003] This invention provides a payment routing method, apparatus, device, and medium based on voiceprint encryption to address the problems of lagging decision-making, insufficient adaptability, and inadequate security in existing cross-border payment routing systems.

[0004] A payment routing method based on voiceprint encryption includes the following steps: acquiring multiple voiceprint key fragments containing voiceprint features and payment information based on a user's voice payment command, and acquiring multiple static key fragments for access authorization; performing routing evaluation on multiple preset cross-border payment paths to obtain a target path for payment settlement; encrypting each of the voiceprint key fragments to obtain multiple anonymous identifiers matching the target path; performing combined verification on each of the voiceprint key fragments and each of the static key fragments according to each of the anonymous identifiers to obtain a routing verification result; and sending the routing verification result and each of the anonymous identifiers to the target path for payment settlement.

[0005] A payment routing device based on voiceprint encryption includes: a segment acquisition module, used to acquire multiple voiceprint key segments containing voiceprint features and payment information, and multiple static key segments for access authorization, based on a user's voice payment command; a routing evaluation module, used to perform routing evaluation on multiple preset cross-border payment paths to obtain a target path for payment settlement; a segment encryption module, used to encrypt each of the voiceprint key segments to obtain multiple anonymous identifiers matching the target path; a combination verification module, used to perform combination verification on each of the voiceprint key segments and each of the static key segments according to each of the anonymous identifiers to obtain a routing verification result; and a payment settlement module, used to send the routing verification result and each of the anonymous identifiers to the target path for payment settlement.

[0006] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the aforementioned payment routing method based on voiceprint encryption.

[0007] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned payment routing method based on voiceprint encryption.

[0008] The aforementioned technical solution for payment routing based on voiceprint encryption, including methods, devices, equipment, and media, comprises the following steps: acquiring multiple voiceprint key fragments containing voiceprint features and payment information, and acquiring multiple static key fragments for access authorization, based on the user's voice payment command; evaluating multiple preset cross-border payment paths to obtain a target path for payment settlement; encrypting each voiceprint key fragment to obtain multiple anonymous identifiers matching the target path; performing combined verification on each voiceprint key fragment and each static key fragment based on each anonymous identifier to obtain a routing verification result; and sending the routing verification result and each anonymous identifier to the target path for payment settlement. This method strengthens the security level of cross-border payment identity authentication through a dual verification mechanism of voiceprint key fragments and static key fragments, effectively resisting risks such as key leakage, man-in-the-middle attacks, and data tampering. It is suitable for the continuous security needs of highly sensitive financial scenarios, supports multi-chain compatibility (such as SWIFT, Ripple, and Corda), and can help financial institutions quickly and seamlessly access mainstream cross-border payment networks, achieving secure interoperability between heterogeneous systems. Attached Figure Description

[0009] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 This is a schematic diagram of an application environment for a payment routing method based on voiceprint encryption according to an embodiment of the present invention; Figure 2 This is a flowchart of a payment routing method based on voiceprint encryption in one embodiment of the present invention; Figure 3 This is a partial flowchart of step S1 in a payment routing method based on voiceprint encryption according to an embodiment of the present invention; Figure 4 This is a specific flowchart of step S2 in a payment routing method based on voiceprint encryption in one embodiment of the present invention; Figure 5 This is a specific flowchart of step S3 in a payment routing method based on voiceprint encryption in one embodiment of the present invention; Figure 6 This is a flowchart illustrating real-time routing evaluation in a payment routing method based on voiceprint encryption according to an embodiment of the present invention. Figure 7 This is a specific flowchart of step S4 in a payment routing method based on voiceprint encryption in one embodiment of the present invention; Figure 8 This is a schematic diagram of a payment routing device based on voiceprint encryption in one embodiment of the present invention; Figure 9 This is a schematic diagram of a computer device according to an embodiment of the present invention. Detailed Implementation

[0011] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0012] The payment routing method based on voiceprint encryption provided in this embodiment of the invention can be applied to, for example... Figure 1 The application environment is shown. Specifically, this voiceprint-based payment routing method is applied in a voiceprint-based payment routing system, which includes, for example, […]. Figure 1The diagram illustrates a client and server that communicate over a network to enable secure data exchange. Through the uniqueness of voiceprint features and a dynamic encryption mechanism, the authentication process is ensured to be uncopyable and tamper-proof, fundamentally preventing impersonation and fraud. The client, also known as the user terminal, is the program that provides local services to the client, corresponding to the server. The client can be installed on, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0013] In one embodiment, such as Figure 2 As shown, a payment routing method based on voiceprint encryption is provided, which is then applied to... Figure 1 Taking the server in the example, the following steps are included: Step S1: Based on the user's voice payment command, obtain multiple voiceprint key fragments containing voiceprint features and payment information, as well as multiple static key fragments for access authorization.

[0014] It should be noted that a user's voice payment instruction is a command issued by the user via voice, containing payment intent and key payment information such as payment amount, target account, and transaction time. Voiceprint key fragments are generated by extracting features from the user's voice payment instruction and binding the voiceprint features and payment information using the user's master key. Each voiceprint key fragment contains a portion of voiceprint features and payment information. Voiceprint features are biometric information in the user's voice, possessing uniqueness and stability. Payment information includes data such as payment amount, target account, and transaction time. Static key fragments are obtained by fragmenting the user's master key, generated and securely stored by a centralized server (or a trusted key management service, KMS), and are pre-stored on the server for verifying access permissions.

[0015] In this embodiment, the process of generating voiceprint key fragments first involves extracting voiceprint features and payment information from the user's voice payment instructions, and then encrypting the payment information to obtain a unique identifier for this payment transaction. Subsequently, based on the user's master key corresponding to the static key fragment, the voiceprint features and the unique identifier are bound together to generate a multi-dimensional encryption vector. This multi-dimensional encryption vector is then split into multiple voiceprint key fragments to ensure that each voiceprint key fragment cannot independently reconstruct the original voiceprint features and payment information, thereby improving data security.

[0016] like Figure 3 As shown, the process of generating voiceprint key fragments includes the following steps: Step S11: Obtain the user's voice payment instruction.

[0017] It should be noted that the user's voice payment command is captured by the client's microphone array, noise-reduced, and then transmitted to the server through an encrypted channel.

[0018] Step S12: Extract features from the user's voice payment instructions to obtain voiceprint features and payment information.

[0019] In this embodiment, the server extracts features from the received user voice payment instructions, separating voiceprint features from payment information. The voiceprint features are extracted and quantized into MFCC feature vectors using Mel-Frequency Cepstral Coefficients (MFCCs), while the payment information is parsed using natural language processing techniques to extract structured data such as payment amount, target account, and transaction time.

[0020] Furthermore, after feature extraction is completed, the voiceprint features are bound to the encrypted payment information, and the process enters the multi-factor key sharding generation stage to ensure that identity authentication and transaction content are protected simultaneously, thereby improving payment security and privacy.

[0021] Step S13: Generate each voiceprint key fragment based on the voiceprint features and payment information.

[0022] It should be noted that the user master key is generated during user registration and securely stored in the hardware security module (HSM). It is invoked when voiceprint key fragments need to be generated and will not be directly exposed to the user or external systems to ensure the security of the voiceprint key fragment generation process.

[0023] In this embodiment, payment information is encrypted using a hash algorithm (such as SHA3-256) to generate a unique identifier for this payment transaction. Then, combined with the user's master key corresponding to each static key fragment, the MFCC feature vector is bound to the unique identifier to generate a multi-dimensional encrypted vector. This multi-dimensional encrypted vector is then fragmented to calculate and generate multiple voiceprint key fragments. This process can be represented as: ; in, For the generated first Each voiceprint key fragment This is the unique identifier for this payment transaction. For the user's master key, For MFCC feature vectors, The number of segments for the voiceprint key. To bind the sharding algorithm.

[0024] In this embodiment, the binding fragmentation algorithm adopts HMAC (Hash-based Message Authentication Code). HMAC is a cryptographic algorithm that combines a key and a hash function to verify the integrity (data has not been tampered with) and authenticity (confirmation of the sender's identity) of a message. A unique identifier serves as the unique identifier for this payment transaction. Binding the voiceprint key fragment to this payment transaction ensures that the voiceprint key fragment is only valid for this payment transaction, preventing replay attacks or key abuse. Simultaneously, each voiceprint key fragment is stored independently on different server nodes, ensuring that if any single node is compromised, the complete voiceprint information cannot be obtained.

[0025] Furthermore, static key fragments can be generated using a high-strength cryptographic random number generator (CSPRNG) and bound to the user's master account or device hardware information, stored in a secure area on the server (such as an HSM) to ensure their unpredictability and uniqueness.

[0026] In this embodiment, the voiceprint key fragmentation includes One, of which ≥3; Static key fragmentation includes One, of which The total number of key fragments and > The static key fragment and the voiceprint key fragment together form a complete payment key required to complete this payment transaction.

[0027] For example, in a scenario where a Chinese seller needs to pay a German supplier €10,000, requiring real-time payment and mitigating exchange rate fluctuation risks, the user's voice payment command is "transfer €10,000 to DE123". After feature extraction, a 40-dimensional MFCC feature vector is extracted from this voice payment command, along with payment information including the payment amount "€10,000", the target account "DE123", and the current transaction timestamp. This payment information is then hashed using SHA3-256 to generate a unique identifier X = Hash("€10,000" + "DE123" + timestamp). Combined with the user's master key K stored in the HSM, a secure multi-party computation protocol maps the MFCC feature vector, H, and the user's master key K to a 512-dimensional encrypted vector V. A secret-sharing scheme is then used to split the 512-dimensional encrypted vector V into three voiceprint key fragments. , and The key fragments are stored in five separate Trusted Execution Environments (TEEs). Each key fragment does not contain complete voiceprint information or key content and must be collaboratively recovered from the original voiceprint features through a threshold reconstruction mechanism in subsequent authentication stages.

[0028] It should be noted that, to ensure dynamic consistency, the voiceprint key fragment is refreshed based on new voiceprint features for each payment to avoid replay attacks.

[0029] In this embodiment, a time-based pseudo-random number generator generates a dynamic obfuscation factor by combining the difference between the current payment timestamp and the previous payment timestamp. This factor is then dynamically obfuscated with the voiceprint key fragment used in the previous payment transaction to obtain the voiceprint key fragment for the current payment transaction, which can be represented as: ; Here, PRNG stands for time-based pseudo-random number generator. This is the current payment timestamp. The timestamp of the last payment. This indicates the segment of the voiceprint key used in the last payment. This indicates a bitwise XOR operation.

[0030] In this embodiment, a dynamic obfuscation factor generated by a time-based pseudo-random number generator is applied to the voiceprint key fragment used in the previous payment transaction, so that the voiceprint key fragment generated in the current payment transaction has a non-linear correlation with the historical fragments in the time dimension, ensuring that the voiceprint key fragment generated each time has temporal randomness and unpredictability, effectively resisting replay attacks and forgery and impersonation risks.

[0031] Step S2: Perform route evaluation on multiple preset cross-border payment paths to obtain the target path for payment settlement.

[0032] It should be noted that the cross-border payment path refers to the existing mainstream cross-border payment networks, including multilateral clearing mechanisms such as SWIFT, CIPS, and mBridge. The target path is the optimal path selected after comprehensively evaluating various cross-border payment paths based on multiple dimensions such as real-time exchange rates, channel stability, transaction fees, and clearing timeliness.

[0033] like Figure 4 As shown, step S2 includes the following sub-steps: Step S21: Assess the overall cost of each cross-border payment path and obtain the overall cost assessment value of each cross-border payment path.

[0034] It should be noted that the comprehensive cost includes real-time exchange rate losses, cross-border transaction fees, capital tied up during the clearing period, and potential exchange rate volatility risk premiums. The comprehensive cost assessment is a quantitative reflection of the overall expenditure level of each cross-border payment route under the current transaction scenario.

[0035] In this embodiment, the comprehensive cost assessment value of each cross-border payment path is formed by comprehensively considering the exchange rate conversion cost, cross-border clearing fees, third-party channel service fees, and the capital occupation cost corresponding to potential exchange loss risks, and by dynamically weighting the calculations based on real-time market data.

[0036] Step S22: Assess the payment risk of each cross-border payment path and obtain the payment risk assessment value for each cross-border payment path.

[0037] It should be noted that payment risk refers to the probability of potential losses caused by uncertainties such as transaction failures, fund freezes, compliance reviews, and anti-money laundering checks that may occur during cross-border payments. The payment risk assessment value is obtained by constructing a multi-dimensional risk scoring model by analyzing the historical success rate of each payment path, the regulatory policies of the host country, the credit rating of the clearing institution, and the real-time network status. This ensures that the target path achieves optimal cost while maintaining high reliability and compliance security.

[0038] In this embodiment, based on real-time comparison of the sanctions list, historical fraud rate and abnormal transaction behavior feature database, combined with the compliance certification level of path nodes and cross-border data message integrity verification mechanism, the payment risk assessment value of each payment path is dynamically output to ensure safe and controllable fund transfer in a complex international regulatory environment.

[0039] Step S23: Evaluate the payment speed of each cross-border payment path and obtain the payment speed evaluation value for each cross-border payment path.

[0040] It should be noted that payment speed refers to the entire process from initiating a transaction to the actual arrival of funds, encompassing clearing and settlement, intermediary bank forwarding, and final confirmation of receipt. The payment speed assessment is dynamically calculated based on historical latency data, current network congestion conditions, and the processing capacity of each node.

[0041] Step S24: Calculate the routing score corresponding to each cross-border payment path based on the comprehensive cost assessment value, payment risk assessment value, and payment speed assessment value.

[0042] It should be noted that the route score is a weighted score calculated based on comprehensive cost assessment, payment risk assessment, and payment speed assessment for each cross-border payment path. A higher route score indicates better overall performance of the path in terms of cost, risk, and speed, and serves as a direct basis for path selection decisions. It is not directly related to the accuracy of user identity verification.

[0043] In this embodiment, the routing score can be expressed as: ; in, , and The first The comprehensive cost assessment value, payment risk assessment value, and payment speed assessment value of each path; , and These are the comprehensive cost assessment values. Payment risk assessment value and payment speed assessment value The weighting coefficients, and .

[0044] In this embodiment, =0.4, =0.4, =0.2.

[0045] It should be noted that the weighting coefficients can be dynamically adjusted based on the current payment transaction priority. For example, high-value transactions are weighted towards cost and risk, while urgent payments are weighted towards speed.

[0046] Step S25: Based on the route scores, select the cross-border payment path with the highest route score as the target path.

[0047] In this embodiment, the first cross-border payment path (SWIFT network) has a comprehensive cost assessment value of €150, a payment risk assessment value of 0.1, a payment speed assessment value of 0.8, and a corresponding routing score of 6.2; the second cross-border payment path (RippleNet network) has a comprehensive cost assessment value of €50, a payment risk assessment value of 0.3, a payment speed assessment value of 0.9, and a corresponding routing score of 7.1; the third cross-border payment path (Stellar network) has a comprehensive cost assessment value of €80, a payment risk assessment value of 0.2, a payment speed assessment value of 0.95, and a corresponding routing score of 7.4.

[0048] This demonstrates that while the SWIFT network has higher path costs and lower risk, its slower payment speed results in a lower routing score compared to the RippleNet and Stellar networks. The Stellar network, with its relatively balanced cost control, lower risk, and higher settlement efficiency, achieved the highest score under the comprehensive weighting allocation, making it the optimal choice. Therefore, the third cross-border payment path (Stellar network) was ultimately selected as the target path for this payment. The payment request was automatically routed to this network, and the path selection result and estimated arrival time were provided in real time. This resulted in an average fee reduction of 60% compared to the first cross-border payment path (SWIFT network), ensuring efficient and secure transaction completion.

[0049] Step S3: Encrypt each voiceprint key fragment to obtain multiple anonymous identifiers that match the target path.

[0050] It should be noted that the encryption process includes asymmetric encryption of each voiceprint key fragment using the public key corresponding to the target payment path, generating corresponding encrypted voiceprint fragments to ensure the confidentiality and integrity of the private key fragments during transmission. Simultaneously, zero-knowledge proof technology is used to anonymize the encrypted voiceprint fragments, obtaining an anonymous identifier compatible with the target path's encryption protocol. This anonymous identifier proves the validity of the corresponding encrypted voiceprint fragment and authorizes the payment transaction, without revealing the original voiceprint characteristics or fragment content, thus completing identity authentication while protecting the user's biometric privacy.

[0051] Specifically, such as Figure 5 As shown, step S3 includes the following sub-steps: Step S31: Based on the target path, pre-encrypt each voiceprint key fragment to generate the corresponding voiceprint encrypted fragment.

[0052] In this embodiment, each voiceprint key fragment is asymmetrically encrypted based on the public key of the Stellar network to generate a corresponding voiceprint encrypted fragment. This ensures that even if the voiceprint encrypted fragment is intercepted by a network eavesdropper during transmission, it cannot be decrypted. Only the target path holding the corresponding private key can decrypt and obtain the plaintext fragment, thus achieving transport layer security.

[0053] Step S32: Anonymize each voiceprint encryption fragment to obtain each anonymous identifier.

[0054] In this embodiment, the zero-knowledge proof mechanism supported by the Stellar network is used to anonymize encrypted fragments, constructing an anonymous identifier compatible with the network protocol. The generation process of the anonymous identifier effectively avoids the risk of sensitive information being exposed on public networks, while ensuring the integrity and privacy of identity verification. This anonymous identifier supports identity consistency verification in cross-chain environments without disclosing the original voiceprint features, increasing the difficulty of transaction tracing by 1000 times and meeting the compliance requirements of high-security scenarios.

[0055] Furthermore, such as Figure 6 As shown, this method also includes the following steps: Step S01: Monitor the real-time status of each cross-border payment path.

[0056] It should be noted that real-time status monitoring covers core indicators such as network latency, transaction confirmation rate, node availability, and encryption protocol compatibility, dynamically capturing path performance fluctuations.

[0057] In this embodiment, risk assessment values ​​for each path are dynamically updated by monitoring sanctions events in real time, including risk factors such as changes in the sanctions list, adjustments to regional financial policies, and network node anomalies.

[0058] Step S02: Based on the real-time status, re-evaluate the routing of each cross-border payment path.

[0059] It's important to note that smart contracts monitor on-chain events (such as node sanctions) to trigger route recalculation. When a node on a certain path is detected to be on the sanctioned list, on-chain status verification is automatically performed. The affected path is then downgraded or blocked based on the latest compliance rules, and the optimal route is recalculated based on the updated scoring matrix. If the originally selected path no longer meets the security threshold, an emergency switching mechanism is immediately activated, dynamically redirecting payment requests to a suboptimal available path to ensure uninterrupted transactions and compliance with regulatory requirements. The entire process requires no manual intervention, enabling autonomous and flexible adjustment of cross-border payment routes and continuous compliance assurance.

[0060] In this embodiment, when a sanction event occurs or the exchange rate fluctuates by more than 5%, route recalculation is triggered. Based on the route evaluation operation in step S2, the route scores of each cross-border payment path are recalculated, prioritizing cross-border payment paths with high route scores that comply with current compliance strategies to ensure payment continuity and legal compliance. If multiple cross-border payment paths have similar scores, a delay-weighted factor is introduced to further optimize the selection and improve overall transmission efficiency.

[0061] Furthermore, when the Stellar network is detected to be officially added to the sanctions list, a sanctions event is triggered, which in turn triggers a route update. This immediately initiates a dynamic rerouting mechanism, recalculates the latest path score to determine the optimal path, and uses threshold signature technology to securely migrate and re-encrypt the voiceprint-encrypted fragments, ensuring that the key fragments are always bound to the currently effective cross-border payment path. When the status of the cross-border payment path changes, the key fragments are automatically re-encrypted and redistributed to ensure they always match the latest routing results, guaranteeing transaction continuity and data confidentiality.

[0062] In this embodiment, the above process avoids sanctioned nodes through dynamic routing, ensuring the compliance and cost controllability of cross-border payment paths, improving the risk resistance of cross-border payments, and increasing the payment success rate from 88% to 99.5%. Moreover, the entire process is completed collaboratively in a distributed environment without centralized intervention, taking into account security, decentralization, and cross-domain interoperability, significantly improving the resilience and adaptability of the cross-border payment system.

[0063] Step S4: Based on each anonymous identifier, perform combined verification on each voiceprint key fragment and each static key fragment to obtain the routing verification result.

[0064] It should be noted that the target path needs to be at least Each voiceprint key fragment (2≤ ≤ ) and all nkOnly a combination of static key fragments is required for decryption, ensuring multi-factor collaborative security for identity authentication. Each anonymous identifier serves as an association index, enabling seamless matching and verification of voiceprint key fragments and avoiding identity association risks in cross-chain environments. The verification process relies on zero-knowledge proof technology to jointly verify the legality of the voiceprint key fragment's source and the integrity of the static key fragments without exposing original biometric features and key information. Only when... Each static key fragment is valid and has at least Only when each voiceprint key fragment passes combined verification can the target path trigger the threshold decryption protocol to reconstruct a valid payment key for payment authorization.

[0065] Specifically, such as Figure 7 As shown, step S4 includes the following sub-steps: Step S41: Select at least two voiceprint key fragments from each voiceprint key fragment as voiceprint verification fragments.

[0066] In this embodiment, at least Each voiceprint key fragment (2≤ ≤ This is a segment for voiceprint verification to ensure that the minimum requirements for threshold decryption are met.

[0067] For example, selecting the voiceprint key fragment mentioned in step S1 and Voiceprint verification segments are used to verify the validity of transactions, ensuring the authenticity of the user's identity and the genuineness of their intention to operate.

[0068] Step S42: Based on the anonymous identifier corresponding to each voiceprint verification segment, perform transaction validity verification on each voiceprint verification segment and obtain the transaction validity verification result.

[0069] It should be noted that transaction validity verification confirms the legitimacy and validity of each voiceprint verification fragment under the target path by verifying the binding relationship between each voiceprint verification fragment and the unique identifier. Combined with a zero-knowledge proof mechanism, the original voiceprint information and key content are not exposed during the verification process, ensuring privacy and security. The transaction validity verification result is the key basis for determining whether the voiceprint verification fragment can be used for subsequent decryption operations. Only after the verification passes and all voiceprint verification fragments are confirmed to be valid is the stage of collaborative decryption with each static key fragment allowed.

[0070] In this embodiment, according to The system uses anonymous identifiers corresponding to each voiceprint verification segment to verify the binding relationship between each voiceprint verification segment and the unique identifier of this payment transaction, thereby obtaining valid voiceprint verification segments and confirming their legitimacy under the current payment path. The verification process is completed using zero-knowledge proofs to ensure that the original voiceprint key segment content and user biometric information are not leaked.

[0071] Step S43: Based on the transaction validity verification results, combine each voiceprint verification fragment and each static key fragment to obtain a valid fragment combination.

[0072] In this embodiment, the legitimate voiceprint verification fragment is only associated with the transaction after all voiceprint verification fragments have passed the transaction validity verification. Each static key fragment is securely combined to construct a complete and effective fragment combination for subsequent collaborative decryption processes.

[0073] Step S44: Perform integrity verification on the valid fragment combination to obtain the routing verification result.

[0074] It should be noted that the route verification result is the key basis for determining whether to allow entry into the next stage of the decryption process. The decryption command for the target path is only triggered when the integrity verification passes and all fragment sources are legitimate and have not been tampered with.

[0075] In this embodiment, the integrity of the valid fragment combination is checked to determine whether the valid fragment combination constitutes all the key fragments required to complete the payment transaction. If the valid fragment combination constitutes all the key fragments required to complete the payment transaction, the decryption instruction of the target path is triggered, and the collaborative decryption process is started. If the valid fragment combination does not constitute all the key fragments required to complete the payment transaction, the decryption process is immediately terminated, the abnormal event is recorded, and a security alarm mechanism is triggered to prevent potential key recombination attacks or data tampering.

[0076] Therefore, the above process can be expressed as: ; in, Indicates user holding A valid voiceprint verification segment; Verify(S_i, TX_hash) represents the verification function used to verify the segment. Unique identifier for this payment transaction Is the binding between them valid? This represents the logical AND operator, indicating that the conditions on both sides must be satisfied simultaneously. express A valid voiceprint verification segment and The static key fragments, when combined, are exactly equal to the payment key required to complete this payment transaction. ; Indicates the first One valid voiceprint verification segment; Indicates the first A static key fragment. The whole equation means that the system can verify that there is indeed a valid set of key fragments that can authorize the transaction, without needing to know what these fragments are specifically.

[0077] Step S5: Send the route verification results and each anonymous identifier to the target path for payment settlement.

[0078] It should be noted that the route verification result includes path security, compliance, and key consistency verification information, ensuring that the target path has undergone full-dimensional trusted verification before executing payment instructions. Each anonymous identifier is dynamically bound to a voiceprint key fragment, ensuring the consistency between identity privacy and transaction traceability.

[0079] In this embodiment, after each anonymous identifier and routing verification result are sent to the target path (Stellar network), the target path makes a final decision based on the received routing verification results. If the routing verification results are valid fragment combinations that form all the key fragments required to complete this payment transaction, the target path determines that this payment transaction meets the decryption and execution conditions, and then initiates a distributed collaborative decryption mechanism. During this process, each static key fragment encrypted with the target path's public key and the corresponding voiceprint encrypted fragment of the verified voiceprint verification fragment are aggregated in a secure computing environment. Based on a threshold cryptography mechanism, a valid payment key is reconstructed, which is used to decrypt the sensitive data required for this payment transaction, thereby completing the payment transaction authorization. This process follows the "zero-knowledge verifiable" principle, ensuring that the key reconstruction behavior is irreversible and has no risk of plaintext exposure.

[0080] Furthermore, once decryption is successful, the target path immediately executes payment settlement and writes the transaction hash to the blockchain ledger, achieving tamper-proof end-to-end traceability. Upon successful decryption, multi-dimensional audit credentials are generated simultaneously, covering the source of voiceprint fragments, the key reassembly path, and node collaboration records, ensuring that every transaction is verifiable, traceable, and non-repudiable. All operation logs are encrypted and uploaded to a distributed storage network in real time to prevent subsequent tampering or leakage. If verification fails at any stage, the system immediately halts the process and activates a circuit breaker mechanism to protect user assets and data security.

[0081] It should be noted that after obtaining each anonymous identifier, the anonymous identifier is submitted to the target path to await the routing verification result for payment settlement. Simultaneously, the voiceprint key fragments and static key fragments are combined and verified using the anonymous identifiers to obtain the routing verification result. After obtaining the routing verification result for all the key fragments required to complete the payment transaction, the routing verification result is sent to the target path, and the generation and distribution of the path-level decryption authorization token are triggered simultaneously, automatically executing the payment settlement.

[0082] In summary, this solution constructs a multi-factor authentication system based on threshold cryptography by dynamically binding voiceprint biometrics with encryption keys. Through collaborative verification of voiceprint key sharding and static key sharding, it ensures the uniqueness and unforgeability of the key reconstruction process, guaranteeing that no single node can obtain complete key information. This achieves a harmonious balance between high security and user privacy and transaction traceability. Specifically, voiceprint key sharding reduces on-chain storage requirements by 70% and gas fees by 50% (Ethereum testing). By determining the target path through routing evaluation, payment latency is reduced from hours to seconds (average 3.2 seconds), supporting real-time foreign exchange hedging and compressing cross-border costs. It is estimated to save small and medium-sized cross-border e-commerce enterprises over 1.2 billion yuan in payment costs annually (estimated based on a trillion-yuan market size). Simultaneously, dynamic routing avoids sanctions lists, achieving real-time compliance verification. The routing verification mechanism is embedded in the entire payment process, ensuring that decryption is only triggered when path security, compliance, and key consistency are all met. This architecture strengthens the security level of identity authentication in cross-border payments through a dual verification mechanism of voiceprint key sharding and static key sharding. It can effectively resist the risks of key leakage, man-in-the-middle attacks and data tampering. It is suitable for the continuous security needs of highly sensitive financial scenarios and supports multi-chain compatibility (such as SWIFT, Ripple, Corda). It can help financial institutions quickly and seamlessly access mainstream cross-border payment networks and achieve secure interoperability between heterogeneous systems.

[0083] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0084] In one embodiment, a payment routing device based on voiceprint encryption is provided, which corresponds one-to-one with the payment routing method based on voiceprint encryption described in the above embodiments. For example... Figure 8 As shown, the payment routing device includes a fragment acquisition module 101, a routing evaluation module 102, a fragment encryption module 103, a combined verification module 104, and a payment settlement module 105. Detailed descriptions of each functional module are as follows: The segment acquisition module 101 is used to acquire multiple voiceprint key segments containing voiceprint features and payment information based on the user's voice payment command, as well as multiple static key segments used for access authorization.

[0085] The routing evaluation module 102 is used to evaluate multiple preset cross-border payment paths to obtain the target path for payment settlement.

[0086] The segmented encryption module 103 is used to encrypt each voiceprint key segment to obtain multiple anonymous identifiers that match the target path.

[0087] The combined verification module 104 is used to perform combined verification on each voiceprint key fragment and each static key fragment based on each anonymous identifier to obtain the routing verification result.

[0088] The payment and settlement module 105 is used to send the route verification results and each anonymous identifier to the target path for payment and settlement.

[0089] Specific limitations regarding the voiceprint-based payment routing device can be found in the above description of the limitations of the voiceprint-based payment routing method, and will not be repeated here. Each module in the aforementioned payment routing device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0090] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 9 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores voiceprint key fragments, static key fragments, and cross-border payment path information. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements a voiceprint-based encryption payment routing method.

[0091] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the voiceprint-based encryption payment routing method described in the above embodiments, for example... Figure 1S1-S5, as shown, will not be described again here to avoid repetition. Alternatively, when the processor executes the computer program, it implements the functions of each module / unit in this embodiment of the voiceprint-based encryption payment routing device, for example... Figure 8 The functions of the fragment acquisition module 101, the route evaluation module 102, the fragment encryption module 103, the combined verification module 104, and the payment settlement module 105 shown are not described again here to avoid duplication.

[0092] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When executed by a processor, the computer program implements the voiceprint-based payment routing method described in the above embodiments, for example... Figure 1 S1-S5, as shown, will not be repeated here to avoid repetition. Alternatively, when this computer program is executed by a processor, it implements the functions of each module / unit in this embodiment of the voiceprint-based encryption payment routing device, for example... Figure 8 The functions of the fragment acquisition module 101, routing evaluation module 102, fragment encryption module 103, combined verification module 104, and payment settlement module 105 shown are not described again here to avoid duplication. The computer-readable storage medium may be non-volatile or volatile.

[0093] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0094] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0095] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A payment routing method based on voiceprint encryption, characterized in that, Including the following steps: Based on the user's voice payment command, obtain multiple voiceprint key fragments containing voiceprint features and payment information, as well as multiple static key fragments used for access authorization; The routing evaluation is performed on multiple preset cross-border payment paths to obtain the target path for payment settlement; Each of the aforementioned voiceprint key fragments is encrypted to obtain multiple anonymous identifiers that match the target path; Based on the anonymous identifiers, the voiceprint key fragments and static key fragments are combined and verified to obtain the routing verification results; The route verification result and each of the anonymous identifiers are sent to the target path for payment settlement.

2. The payment routing method according to claim 1, characterized in that, The step of performing route evaluation on multiple preset cross-border payment paths to obtain a target path for payment settlement includes: The comprehensive cost of each of the aforementioned cross-border payment paths is evaluated to obtain a comprehensive cost assessment value for each of the aforementioned cross-border payment paths; The payment risk of each of the aforementioned cross-border payment paths is assessed to obtain the payment risk assessment value for each of the aforementioned cross-border payment paths; The payment speed of each of the aforementioned cross-border payment paths is evaluated to obtain the payment speed evaluation value for each of the aforementioned cross-border payment paths; Based on the comprehensive cost assessment value, the payment risk assessment value, and the payment speed assessment value, calculate the routing score corresponding to each cross-border payment path; Based on the routing scores, the cross-border payment path with the highest routing score is selected as the target path.

3. The payment routing method according to claim 1, characterized in that, The encryption process performed on each of the voiceprint key fragments to obtain multiple anonymous identifiers matching the target path includes: According to the target path, each of the voiceprint key fragments is pre-encrypted to generate the corresponding voiceprint encrypted fragments; Each of the aforementioned voiceprint encryption fragments is anonymized to obtain the aforementioned anonymous identifier.

4. The payment routing method according to claim 1, characterized in that, The step of combining and verifying each voiceprint key fragment and each static key fragment according to each anonymous identifier to obtain a routing verification result includes: Select at least two of the aforementioned voiceprint key fragments as voiceprint verification fragments; Based on the anonymous identifier corresponding to each of the voiceprint verification segments, the transaction validity is verified for each of the voiceprint verification segments, and the transaction validity verification result is obtained. Based on the transaction validity verification results, each of the voiceprint verification segments and each of the static key segments are combined to obtain an effective segment combination; Integrity verification is performed on the valid fragment combination to obtain the routing verification result.

5. The payment routing method according to claim 1, characterized in that, The process of obtaining multiple voiceprint key fragments containing voiceprint features and payment information based on user voiceprint payment instructions includes: Obtain the user's voice payment instruction; Feature extraction is performed on the user's voice payment command to obtain the voiceprint features and payment information; Based on the voiceprint features and payment information, each voiceprint key fragment is generated.

6. The payment routing method according to claim 5, characterized in that, The step of generating each of the voiceprint key fragments based on the voiceprint features and payment information includes: The payment information is encrypted to generate a unique identifier for payment settlement; The voiceprint feature and the unique identifier are bound together to generate a multi-dimensional encryption vector; The multidimensional encryption vector is fragmented to obtain each of the voiceprint key fragments.

7. The payment routing method according to claim 1, characterized in that, The payment routing method further includes: Monitor the real-time status of each of the aforementioned cross-border payment paths; Based on the real-time status of each item, the routing of each cross-border payment path is re-evaluated.

8. A payment routing device based on voiceprint encryption, characterized in that, include: The segment acquisition module is used to acquire multiple voiceprint key segments containing voiceprint features and payment information based on the user's voice payment command, as well as multiple static key segments used for access authorization. The routing evaluation module is used to evaluate multiple preset cross-border payment paths to obtain the target path for payment settlement. The segmented encryption module is used to encrypt each of the voiceprint key segments to obtain multiple anonymous identifiers that match the target path. The combined verification module is used to perform combined verification on each of the voiceprint key fragments and each of the static key fragments based on each of the anonymous identifiers to obtain the routing verification result; The payment settlement module is used to send the route verification result and each of the anonymous identifiers to the target path for payment settlement.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the payment routing method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the payment routing method as described in any one of claims 1 to 7.

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