Aggregate payment method, device, equipment, medium and program product

Abstract

The invention provides an aggregation payment method and device, equipment, a medium and a program product, and relates to the technical field of mobile payment, and the method applied to an identity verification platform comprises the steps: when a user initiates an aggregation payment request to an aggregation payment platform, according to the user identity information sent by the aggregation payment platform, sending the aggregation payment request to the aggregation payment platform; executing multi-dimensional risk assessment on the user to obtain an initial risk score; according to the initial risk score, executing multi-dimensional identity verification on the user to obtain an identity verification result; and sending the identity verification result to the aggregation payment platform. According to the scheme of the application, the security of identity verification in an aggregation payment scene is significantly improved.

Description

Technical Field

[0001] This application relates to the field of mobile payment technology, specifically to an aggregated payment method, device, equipment, medium, and program product. Background Technology

[0002] With the widespread adoption of mobile payments, aggregated payment platforms face increasingly complex security challenges and user experience demands. Users expect convenient payments along with a higher level of security and privacy protection. To address this, existing aggregated payment platforms employ technologies such as centralized identity storage, fixed-weight multi-factor authentication, single-dimensional identity verification, traditional encrypted transmission, and fixed payment verification processes. However, these solutions suffer from single-point-of-failure risks, making them vulnerable to hacker attacks and posing security risks. Furthermore, the static identity verification process struggles to handle complex and ever-changing fraud scenarios, also presenting security risks. Summary of the Invention

[0003] This application provides an aggregated payment method, apparatus, device, medium, and program product to address the security risks inherent in existing aggregated payment methods.

[0004] To solve the above-mentioned technical problems, this application is implemented as follows:

[0005] Firstly, this application provides an aggregated payment method applied to an identity verification platform, the method comprising:

[0006] When a user initiates an aggregated payment request to the aggregated payment platform, a multi-dimensional risk assessment is performed on the user based on the user identity information sent by the aggregated payment platform to obtain an initial risk score;

[0007] Based on the initial risk score, multi-dimensional identity verification is performed on the user to obtain the identity verification result;

[0008] Send the identity verification result to the aggregated payment platform.

[0009] Optionally, in the aggregated payment method, based on the user identity information sent by the aggregated payment platform, a multi-dimensional risk assessment is performed on the user to obtain an initial risk score, including:

[0010] The user identity information sent by the aggregated payment platform is reconstructed to obtain the reconstructed user identity information;

[0011] Based on the reconstructed user identity information, a multi-dimensional risk assessment is performed on the user to obtain an initial risk score.

[0012] Optionally, in the aggregated payment method, reconstructing the user identity information sent by the aggregated payment platform to obtain the reconstructed user identity information includes:

[0013] Based on the user identity information sent by the aggregated payment platform, an encrypted user identity fragment is obtained;

[0014] The user private key fragment in the user identity information is reconstructed based on the encrypted user identity fragment to obtain the reconstructed user private key fragment.

[0015] The reconstructed user identity information is obtained by performing an XOR operation on the encrypted user identity fragment and the reconstructed user private key fragment.

[0016] Optionally, in the aggregated payment method, obtaining the reconstructed user identity information by performing an XOR operation on the encrypted user identity fragment and the reconstructed user private key fragment includes:

[0017] Based on the reconstructed user private key fragment, the encrypted user identity fragment is decrypted to obtain the decrypted user identity fragment;

[0018] Perform an XOR operation on multiple decrypted user identity fragments to obtain the first user identity information;

[0019] An XOR operation is performed on the first user identity information and the first hash function value to obtain the reconstructed user identity information. The first hash function value is obtained based on the user's unique identifier in the user identity information.

[0020] Optionally, in the aggregated payment method, based on the reconstructed user identity information, a multi-dimensional risk assessment is performed on the user to obtain an initial risk score, including:

[0021] Based on the reconstructed user identity information, user transaction characteristics are obtained;

[0022] For predefined multi-dimensional risk factors, a score for each risk factor is obtained based on the user's trading characteristics corresponding to each risk factor.

[0023] An initial risk score is obtained based on the time interval since the last successful authentication, the predefined impact coefficient, the time-sensitive item coefficient, the maximum timeout threshold, and the weight and score of each risk factor.

[0024] Optionally, in the aggregated payment method, performing multi-dimensional identity verification on the user based on the initial risk score to obtain the identity verification result includes:

[0025] For predefined multi-dimensional authentication, the dynamic weight of each authentication dimension is obtained based on the initial risk score;

[0026] A score for each dimension of authentication is obtained based on the dynamic weight of each dimension of authentication.

[0027] An identity verification result is obtained based on the score for each dimension of identity verification and the user's aggregated payment characteristic score. Secondly, this application also provides an aggregated payment method applied to an aggregated payment platform, the method comprising:

[0028] Upon obtaining the user's authentication result from the authentication platform and sending the authentication result to the user, the aggregated payment data sent by the user is irreversibly transformed to obtain the transformed aggregated payment data.

[0029] Send the transformed aggregated payment data to the payment verification platform;

[0030] Obtain the payment processing result sent by the payment verification platform;

[0031] The payment processing result is sent to the user.

[0032] Optionally, in the aggregated payment method, performing an irreversible transformation on the aggregated payment data sent by the user to obtain transformed aggregated payment data includes:

[0033] The aggregated payment data sent by the user is irreversibly transformed according to a predefined irreversible transformation function to obtain the transformed aggregated payment data. The irreversible transformation function includes at least one of secure hash operation, pseudo-random number generation operation, bitwise XOR operation, and cyclic shift operation.

[0034] Thirdly, this application also provides an aggregated payment method applied to a payment verification platform, the method comprising:

[0035] Upon receiving the transformed aggregated payment data sent by the aggregated payment platform, the transformed aggregated payment data is recovered to obtain the recovered aggregated payment data.

[0036] Based on the recovered aggregated payment data, perform multi-dimensional payment verification to obtain the payment verification result;

[0037] Based on the payment verification result, the payment is processed to obtain the payment processing result;

[0038] The payment processing result is sent to the aggregated payment platform.

[0039] Optionally, in the aggregated payment method, data recovery of the transformed aggregated payment data to obtain recovered aggregated payment data includes:

[0040] The integrity of the transformed aggregated payment data is verified to obtain the integrity verification result;

[0041] If the integrity verification result is passed, the aggregated payment data of the transformation is restored according to the inverse operation of the predefined irreversible transformation function to obtain the restored aggregated payment data. The irreversible transformation function includes at least one of the following: secure hash operation, pseudo-random number generation operation, bitwise XOR operation, and cyclic shift operation.

[0042] Optionally, the aggregated payment method, wherein performing multi-dimensional payment verification based on the recovered aggregated payment data to obtain a payment verification result includes:

[0043] Based on the payment type in the recovered aggregated payment data, obtain multi-dimensional payment verification rules related to the payment type;

[0044] Based on the recovered aggregated payment data, obtain the verification function value corresponding to the payment verification rule for each dimension;

[0045] The payment verification result is obtained based on the verification function value corresponding to the payment verification rule for each dimension.

[0046] Fourthly, this application also provides an aggregated payment device for use in an identity verification platform, the device comprising:

[0047] The risk assessment module is used to perform a multi-dimensional risk assessment on the user based on the user identity information sent by the aggregated payment platform when the user initiates an aggregated payment request to the aggregated payment platform, and obtain an initial risk score;

[0048] An identity verification module is used to perform multi-dimensional identity verification on the user based on the initial risk score and obtain an identity verification result;

[0049] The first sending module is used to send the identity verification result to the aggregated payment platform.

[0050] Fifthly, this application also provides an aggregated payment device for use on an aggregated payment platform, the device comprising:

[0051] The transformation module is used to irreversibly transform the aggregated payment data sent by the user when the user's authentication result is obtained from the authentication platform and the authentication result is sent to the user, so as to obtain the transformed aggregated payment data.

[0052] The second sending module is used to send the transformed aggregated payment data to the payment verification platform;

[0053] The first acquisition module is used to acquire the payment processing result sent by the payment verification platform;

[0054] The third sending module is used to send the payment processing result to the user.

[0055] Sixthly, this application also provides an aggregated payment device for use in a payment verification platform, the device comprising:

[0056] The recovery module is used to recover the transformed aggregated payment data sent by the aggregated payment platform when the transformed aggregated payment data is obtained, so as to obtain the recovered aggregated payment data.

[0057] The payment verification module is used to perform multi-dimensional payment verification based on the recovered aggregated payment data and obtain the payment verification result;

[0058] The second acquisition module is used to perform payment processing based on the payment verification result and acquire the payment processing result.

[0059] The fourth sending module is used to send the payment processing result to the aggregated payment platform.

[0060] In a seventh aspect, this application also provides an aggregated payment device, comprising: a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the processor executes the program or instructions to implement the aggregated payment method as described in the first, second, or third aspect.

[0061] Eighthly, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the aggregated payment method as described in the first, second, or third aspect.

[0062] Ninthly, this application also provides a computer program product, including computer instructions that, when executed by a processor, implement the aggregated payment method as described in the first, second, or third aspects.

[0063] Compared with existing technologies, the aggregated payment method for identity verification platforms provided in this application, when a user initiates an aggregated payment request to the aggregated payment platform, performs a multi-dimensional risk assessment on the user based on the user identity information sent by the aggregated payment platform to obtain an initial risk score; performs multi-dimensional identity verification on the user based on the initial risk score to obtain an identity verification result; and sends the identity verification result to the aggregated payment platform. This achieves multi-dimensional interactive verification of user identity information, effectively solves security risks, and significantly improves the security, privacy protection level, accuracy, and adaptability of identity verification in aggregated payment scenarios. Attached Figure Description

[0064] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0065] Figure 1 This is a flowchart illustrating the aggregated payment method described in the first embodiment of this application;

[0066] Figure 2 This is a schematic diagram illustrating the method for calculating the initial risk score as described in an embodiment of this application;

[0067] Figure 3 This is a flowchart illustrating the first implementation of the aggregated payment method described in this application.

[0068] Figure 4 This is a schematic diagram of the interface for the authentication result described in the embodiments of this application;

[0069] Figure 5 This is a flowchart illustrating the aggregated payment method described in the second embodiment of this application;

[0070] Figure 6 This is a flowchart illustrating the aggregated payment method described in the third embodiment of this application;

[0071] Figure 7 This is a flowchart illustrating a second implementation of the aggregated payment method described in the embodiments of this application;

[0072] Figure 8 This is a schematic diagram of the interface for the payment processing result described in the embodiments of this application;

[0073] Figure 9 This is a flowchart illustrating the third implementation of the aggregated payment method described in the embodiments of this application;

[0074] Figure 10This is a schematic diagram of the aggregated payment device described in the first embodiment of this application;

[0075] Figure 11 This is a schematic diagram of the aggregated payment device described in the second embodiment of this application;

[0076] Figure 12 This is a schematic diagram of the aggregated payment device described in the third embodiment of this application;

[0077] Figure 13 This is a hardware block diagram of the aggregated payment device described in the embodiments of this application. Detailed Implementation

[0078] The terms "first," "second," etc., used in this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first" and "second" are generally of the same class, without limiting the number of objects; for example, the first object can be one or more. Furthermore, "or" in this application indicates at least one of the connected objects. For example, "A or B" covers three scenarios: Scenario 1: including A but not B; Scenario 2: including B but not A; Scenario 3: including both A and B. The character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0079] Please refer to Figure 1 This application provides an aggregated payment method applied to an identity verification platform, the method comprising:

[0080] Step 101: When a user initiates an aggregated payment request to the aggregated payment platform, a multi-dimensional risk assessment is performed on the user based on the user identity information sent by the aggregated payment platform to obtain an initial risk score;

[0081] In this embodiment of the application, optionally, the user initiates an aggregated payment request to the aggregated payment platform, including:

[0082] Users scan the aggregated payment QR code through a payment client (such as the Hebao client) to initiate an aggregated payment request to the aggregated payment platform.

[0083] Furthermore, the aggregated payment platform forwards the user's identity information carried in the aggregated payment request to the identity verification platform. This step is the identity verification process when a user initiates an aggregated payment request, and it aims to ensure the legality and security of the payment.

[0084] Optionally, the aggregated payment platform forwards the aggregated payment request to the identity verification platform. This aggregated payment request carries user identity information and is used to request user identity verification.

[0085] Optionally, the aggregated payment platform sends a user authentication request to the identity verification platform. This user authentication request carries user identity information and is used to request user authentication.

[0086] The identity verification platform obtains user identity information and performs identity verification, including step 101.

[0087] Optionally, the user identity information includes at least one of the following:

[0088] User's unique identifier ID; User's mobile phone number information; User's private key fragment User equipment information identifier (ID); current geographical location (latitude and longitude); current transaction time.

[0089] In one implementation method, optionally, a multi-dimensional risk assessment is performed on the user based on the user identity information sent by the aggregated payment platform to obtain an initial risk score, including:

[0090] The user identity information sent by the aggregated payment platform is reconstructed to obtain the reconstructed user identity information;

[0091] Based on the reconstructed user identity information, a multi-dimensional risk assessment is performed on the user to obtain an initial risk score.

[0092] It should be noted that the identity verification platform employs Distributed Identity Reconstruction Technology (DIRT), which includes: reconstructing the user identity information sent by the aggregated payment platform to obtain reconstructed user identity information, thereby improving the security and privacy protection level of user identity information. Specifically, it includes steps a to e in the following embodiments.

[0093] In one implementation method, optionally, the user identity information sent by the aggregated payment platform is reconstructed to obtain the reconstructed user identity information, including:

[0094] Based on the user identity information sent by the aggregated payment platform, an encrypted user identity fragment is obtained;

[0095] The user private key fragment in the user identity information is reconstructed based on the encrypted user identity fragment to obtain the reconstructed user private key fragment.

[0096] The reconstructed user identity information is obtained by performing an XOR operation on the encrypted user identity fragment and the reconstructed user private key fragment.

[0097] Optionally, based on the user identity information sent by the aggregated payment platform, an encrypted user identity fragment is obtained, including:

[0098] Step a, Initialization:

[0099] Create an authentication session and generate a unique session ID;

[0100] Generate a random number r.

[0101] Step b, Fragment retrieval: For user u, retrieve K encrypted user identity fragments F1, F2, ..., F from distributed storage based on the user's unique identifier ID and mobile phone number information. K .

[0102] Optionally, the user private key fragment in the user identity information is reconstructed based on the encrypted user identity fragment to obtain the reconstructed user private key fragment, including:

[0103] Step c, merge the private key: extract the user's private key fragment from the user's identity information. The encrypted user identity fragment retrieved from the distributed storage is reconstructed and merged to obtain the reconstructed user private key fragment SK. u The reconstruction and merging can utilize existing technologies (such as the Shamir secret sharing algorithm). The reconstructed user private key fragment SK... u This is a type of private key that exists only temporarily in memory and is used for the current authentication process. Once authentication is complete, the reconstructed user private key fragment needs to be securely erased from memory immediately, and the system will periodically (e.g., every six months) require the user to update their reconstructed user private key fragment.

[0104] In one implementation, optionally, an XOR operation is performed on the encrypted user identity fragment and the reconstructed user private key fragment to obtain the reconstructed user identity information, including:

[0105] Based on the reconstructed user private key fragment, the encrypted user identity fragment is decrypted to obtain the decrypted user identity fragment;

[0106] Perform an XOR operation on multiple decrypted user identity fragments to obtain the first user identity information;

[0107] An XOR operation is performed on the first user identity information and the first hash function value to obtain the reconstructed user identity information. The first hash function value is obtained based on the user's unique identifier in the user identity information carried in the aggregated payment request.

[0108] Specifically, the reconstructed user identity information is obtained by performing an XOR operation on the encrypted user identity fragment and the reconstructed user private key fragment, including:

[0109] Step d, Fragment decryption: Based on the reconstructed user private key fragment SK u For each encrypted user identity fragment retrieved in step b above, perform the following decryption operation to obtain the decrypted user identity fragment:

[0110] Dec(F k SK u )

[0111] Where Dec is the decryption function; SK u It is a reconstructed fragment of the user's private key for user u.

[0112] Step e, Identity Information Reconstruction: Apply the core algorithm formula in DIRT to reconstruct the identity information and obtain the reconstructed user identity information:

[0113]

[0114] This process includes:

[0115] Perform the following XOR operation on all decrypted user identity fragments to obtain the first user identity information:

[0116]

[0117] Where K is the total number of user identity fragments; F k It is the k-th encrypted user identity fragment; ⊕ represents the XOR operation.

[0118] Calculate the value of the first hash function:

[0119] H(u|r)

[0120] Where H is a hash function; | represents string concatenation; u represents the user's unique identifier ID; and r is the random number generated in step a above.

[0121] The first user identity information and the first hash function value are XORed again to obtain the reconstructed user identity information ID(u).

[0122] For example, a typical reconstructed user identity information ID(u) data structure is as follows:

[0123]

[0124] It should be noted that, considering that centralized storage of user identity information in aggregated payment systems makes them vulnerable to attacks, and that existing data encryption technologies suffer from drawbacks such as complex key management and performance bottlenecks during decryption, the identity verification platform in this embodiment adopts DIRT. DIRT achieves secure storage and efficient retrieval of user identity information through distributed storage, dynamic reconstruction, and temporary session keys, solving the security vulnerabilities and performance bottlenecks of traditional centralized storage, and significantly improving the system's security and scalability.

[0125] In one implementation method, optionally, a multi-dimensional risk assessment is performed on the user based on the reconstructed user identity information to obtain an initial risk score, including:

[0126] Based on the reconstructed user identity information, user transaction characteristics are obtained;

[0127] For predefined multi-dimensional risk factors, a score for each risk factor is obtained based on the user transaction characteristics corresponding to each risk factor.

[0128] An initial risk score is obtained based on the time interval since the last successful authentication, the predefined impact coefficient, the time-sensitive item coefficient, the maximum timeout threshold, and the weight and score of each risk factor.

[0129] Optionally, based on the reconstructed user identity information, user transaction characteristics are obtained, including:

[0130] Extract key features F from the verified session object and the reconstructed user identity information ID(u). i In other words, user transaction characteristics, which include at least one of the following:

[0131] Historical transaction time; historical transaction location; historical transaction equipment.

[0132] Optional, predefined multidimensional risk factors, including at least one of the following:

[0133] Equipment risk factors; time risk factors; location risk factors; aggregated payment risk factors.

[0134] Therefore, the scoring of multidimensional risk factors includes at least one of the following:

[0135] Scoring of equipment risk factors; scoring of time risk factors; scoring of location risk factors; scoring of aggregated payment risk factors.

[0136] The device risk factor score is obtained based on the user transaction characteristics corresponding to the device risk factor and the scoring function of the device risk factor.

[0137] Optionally, the user transaction characteristics corresponding to the device risk factor include at least one of the following:

[0138] Device fingerprint similarity distance; operating system version differences; browser version differences.

[0139] Optionally, the scoring function for the equipment risk factor is as follows:

[0140] g1(F device )=1-exp(-λ d ·(w1·d fp +w2·d os +w3·d br ))

[0141] Among them, F device It is a combination of user equipment characteristic values;

[0142] λ d It is a parameter related to equipment risk sensitivity;

[0143] d fp It is the device fingerprint similarity distance.

[0144] d os This is due to differences in operating system versions; the absolute value of the difference is taken.

[0145] d br This is due to differences in browser versions; the absolute value of the difference is taken.

[0146] w1, w2, w3 are the weights of each sub-factor, and w1 + w2 + w3 = 1;

[0147] The time risk factor score is obtained based on the user's trading characteristics corresponding to the time risk factor and the scoring function of the time risk factor.

[0148] Optionally, the user trading characteristics corresponding to the time risk factor include at least one of the following:

[0149] Current trading time; user's historical trading time; current trading frequency.

[0150] Optionally, the scoring function for the time risk factor is as follows:

[0151]

[0152] Among them, F time It is a combination of user transaction time feature values;

[0153] t is the current trading time, converted to minutes in a day;

[0154] u t It is the average time of a user's historical transactions;

[0155] σ t It is the standard deviation of the user's historical transaction time;

[0156] f t This refers to the current trading frequency, such as the number of transactions in the past hour.

[0157] f0 is the threshold for the normal transaction frequency of users;

[0158] x is the tradeoff coefficient between time anomalies and frequency anomalies;

[0159] 0≤α≤1;

[0160] y is the frequency sensitivity parameter.

[0161] The location risk factor score is obtained based on the user transaction characteristics corresponding to the location risk factor and the location risk factor scoring function.

[0162] Optionally, the user transaction characteristics corresponding to the location risk factor include at least one of the following:

[0163] Geographic location; the areas where users frequently operate.

[0164] Optionally, the scoring function for the location risk factor is as follows:

[0165] g3(F location ) = w g ·g geo +w p ·g pattern

[0166] Among them, F location It is a combination of user transaction location feature values;

[0167] w g ,w p It is the weight of the sub-factors of geographical location and matching degree, and w g +w p =1;

[0168] Geographic location subfunction g geo =1-exp(-λ g ·d hav (loc current当前位置 ,loc usual常驻位置 )), where d hav It is the Havel-Syne distance between two geographic coordinates, λ g It is a geographic sensitivity parameter;

[0169] Matching degree subfunction Where C i It is the user's i-th frequently used location cluster, wi It is the weight of the cluster at that location. It is an indicator function that returns 1 or 0. n represents the total number of location clusters identified in the user's historical activities, with each cluster representing an area where the user frequently operates.

[0170] The score for the aggregated payment risk factor is obtained based on the user transaction characteristics corresponding to the aggregated payment risk factor and the scoring function of the aggregated payment risk factor.

[0171] Optionally, the user transaction characteristics corresponding to the aggregated payment risk factor include at least one of the following:

[0172] The current payment platform combination used in the transaction; the commonly used payment platform combination.

[0173] The scoring function for the aggregated payment risk factor is as follows:

[0174] g4(F aggregation )=1-exp(-η·|P current -P usual |)

[0175] Among them, F aggregation It is a combination of feature values ​​from user-scanned payment aggregation platforms;

[0176] P current This is the number of payment platform combinations used in the current transaction (e.g., WeChat Pay, Alipay, UnionPay);

[0177] P usual η is the number of payment platform combinations that users typically use; η is the sensitivity parameter.

[0178] It should be noted that the aggregated payment risk factor assesses the degree of deviation between the user's current combination of payment platforms and their usual behavior.

[0179] Figure 2 This is a schematic diagram illustrating the method for calculating the initial risk score as described in the embodiments of this application; as follows: Figure 2 As shown, the initial risk score R is calculated as follows:

[0180]

[0181] Where n is the number of risk factors considered, which is predefined by the business based on the dimensions of the collected user data. Here, n is preset to 4, and the corresponding risk factors are calculated around device, location, time, and aggregated payment characteristics.

[0182] α i It is the weight of the i-th risk factor;

[0183] β is a predefined influence coefficient;

[0184] CRWF is a comprehensive risk-weighted term that calculates a weighted average of the squares of the scores for risk factors, emphasizing the impact of high-risk factors. The calculation formula is as follows:

[0185]

[0186] Where n is the number of risk factors;

[0187] w i It is the weight of the i-th risk factor;

[0188] g i (F i ) is the scoring function for the i-th risk factor;

[0189] γ is a predefined coefficient for the time-sensitive term;

[0190] Δt is the time interval since the last successful authentication;

[0191] t0 is the maximum timeout threshold, which is predefined by the business logic;

[0192] g i (F i F is the scoring function for the i-th risk factor. i This is the corresponding subset of user features. The calculation formulas for each scoring function are as described above and will not be repeated here.

[0193] Step 102: Perform multi-dimensional identity verification on the user based on the initial risk score to obtain the identity verification result;

[0194] In one implementation method, optionally, multi-dimensional identity verification is performed on the user based on the initial risk score to obtain an identity verification result, including:

[0195] For predefined multi-dimensional authentication, the dynamic weight of each authentication dimension is obtained based on the initial risk score;

[0196] A score for each dimension of authentication is obtained based on the dynamic weight of each dimension of authentication.

[0197] The authentication result is obtained based on the score for each dimension of authentication and the user's aggregated payment characteristic score.

[0198] It should be noted that the authentication platform uses a Dynamic Weighted Multi-dimensional Authentication System (DWMAS), which includes: for predefined multi-dimensional authentication, obtaining the dynamic weight of each dimension of authentication based on the initial risk score.

[0199] Optional, predefined multidimensional authentication includes at least one of the following:

[0200] Verification of consistency across multiple platforms; cross-verification of payment channels; verification of dynamic transaction limits.

[0201] By applying the core weight calculation formula in DWMAS, the dynamic weight of each dimension of authentication is obtained:

[0202] w i =w i,base ·(1+α·sigmoid(β·(R-R0)))·exp(-γ·t i )

[0203] This formula calculates the dynamic weight w of the i-th dimension of identity verification (including three dimensions of identity verification: multi-platform behavior consistency verification, payment channel cross-verification, and dynamic transaction limit verification). i .

[0204] w i,base This is the base weight for the i-th dimension of authentication. The preset base weights for the three dimensions of authentication are as follows:

[0205] Multi-platform behavior consistency verification w 1,base =0.4, this verification is used to compare user behavior patterns on different payment platforms to ensure consistency of behavior across platforms;

[0206] Payment channel cross-validation w 2,base =0.3, this verification is used to verify a user's ability to use multiple payment channels and to assess the credibility of the user's identity;

[0207] Dynamic transaction limit verification w 3,base =0.3, this verification is based on the user's historical transaction data, dynamically adjusting and verifying whether the current transaction exceeds the personalized limit;

[0208] α is the sensitivity coefficient for weight adjustment;

[0209] β is the adjustment coefficient that controls the sigmoid function;

[0210] R is the initial risk score;

[0211] R0 is the baseline risk score, defined during business initialization;

[0212] γ is the time decay coefficient;

[0213] t i It is the time since the last authentication in the i-th dimension;

[0214] Specifically, the execution process of DWMAS includes:

[0215] Risk assessment: Calculate the initial risk score R;

[0216] For authentication of the i-th dimension: obtain the basic weight w i,base Calculate the time t since the last use of this factor. i Risk adjustment is performed using the sigmoid function, and a time decay factor is applied to calculate the final dynamic weight w. i ;

[0217] Normalization: Ensures that the sum of all dynamic weights is 1.

[0218] It should be noted that, considering the varying importance of verification factors across different scenarios, existing fixed-weight authentication systems suffer from insufficient flexibility and difficulty in adapting to complex and ever-changing risk environments. Therefore, this application adopts DWMAS in its embodiments. DWMAS utilizes techniques such as real-time risk scoring, adaptive weight adjustment, and multi-dimensional feature analysis to achieve dynamic optimization of verification factor weights, solving the problem of slow response to risk changes in static weight systems and greatly enhancing the adaptability and effectiveness of the identity verification system.

[0219] It should also be noted that the identity verification platform adopts a multi-dimensional interactive verification fusion model (MIVM), which includes obtaining a credibility score based on the score of each dimension of identity verification and the user's aggregated payment characteristics score.

[0220] Furthermore, the credibility score is compared with a preset credibility threshold to obtain an authentication result, which includes pass or rejection (fail).

[0221] By applying the core formula of MIVM, the credibility score is obtained:

[0222]

[0223] This formula calculates the credibility score of user u in transaction t.

[0224] u represents the user, which is the unique identifier ID of the user currently undergoing authentication;

[0225] t represents the timestamp of the current transaction or verification session;

[0226] w i It is the dynamic weight of the i-th dimension of identity verification;

[0227] f i (x i ,h i ) is the scoring function for the i-th dimension authentication, used to obtain the score for the i-th dimension authentication, x i This is the input for this transaction, h i It is historical data.

[0228] That is, obtain the score for each dimension of authentication based on the scoring function of each dimension of authentication.

[0229] Optional scoring function for multi-platform behavioral consistency verification:

[0230] f1(x1,h1)=1-exp(-λ1·sim(x1,h1))

[0231] Here, sim(x1,h1) is the similarity between the current user's behavioral characteristics (payment amount) and historical behavior (average payment amount) on different payment platforms, which can be calculated using the cosine similarity formula.

[0232] Optional scoring function for payment channel cross-validation:

[0233]

[0234] Where n is the number of different payment channels that the user can currently successfully activate; n0 is the preset threshold; and α is the adjustment factor.

[0235] Optional scoring function for dynamic transaction limit verification:

[0236]

[0237] Where x3 is the current transaction amount; L(h3) is the dynamic limit calculated based on the user's historical transactions; and β is the sensitivity parameter.

[0238] Optionally, a user's aggregated payment characteristic score can be obtained based on a scoring function of aggregated payment characteristics.

[0239] AP(u,t): The scoring function for aggregated payment characteristics, defined as follows:

[0240]

[0241] Wherein, D(u) represents the diversity index of payment platforms used by users. This index reflects the degree of diversity of different payment methods used by users on aggregated payment platforms. It can be replaced by the number of available payment channels. The higher the value, the more diverse the payment methods used by users.

[0242] μ is a diversity sensitivity parameter;

[0243] t is the current time;

[0244] T is a periodic constant, such as 24 hours.

[0245] ω is the weighting coefficient of the scoring function for aggregated payment characteristics, used to adjust the degree of influence of aggregated payment characteristics on the total score;

[0246] Specifically, the execution process of MIVM includes:

[0247] Initialize the parameters for multi-dimensional authentication;

[0248] For authentication of the i-th dimension: obtain the current input x i and historical data h i Calculate factor scores f i (x i ,h i ), obtain dynamic weight w i ;

[0249] Calculate the aggregated payment characteristic score AP(u,t).

[0250] Calculate the confidence score MIVM(u,t).

[0251] It should be noted that, considering that traditional aggregated payment identity verification methods often rely on a single dimension for evaluation and are ill-equipped to handle complex fraud scenarios, and that existing multi-factor authentication technologies suffer from insufficient correlation between factors and poor adaptability, this application adopts MIVM. MIVM achieves comprehensive and dynamic verification of user identity through dynamic weight allocation, feature fusion of multi-dimensional verification methods (fusion and calculation, multi-platform behavior consistency verification, payment channel cross-verification, and behavior scores under dynamic transaction limits), solving the limitations of single-dimensional verification and the vulnerability of static verification, thus significantly improving the accuracy and security of identity verification.

[0252] Figure 3 This is a flowchart illustrating the first implementation of the aggregated payment method described in this application. Figure 3 As shown, the method includes:

[0253] Step 301: Reconstruct the user identity information using DIRT;

[0254] Step 302: Extract user transaction features from the reconstructed user identity information;

[0255] Step 303: Based on the user's transaction characteristics, perform a multi-dimensional risk assessment on the user to obtain an initial risk score R;

[0256] Step 304: Use DWMAS to calculate the dynamic weight of authentication for each dimension;

[0257] Step 305: Calculate the confidence score using MIVM;

[0258] Step 306: Compare the credibility score with the preset credibility threshold to determine whether the identity verification is successful;

[0259] Step 307: Identity verification passed; return successful result.

[0260] Step 308: Authentication failed; rejection result returned.

[0261] Step 103: Send the identity verification result to the aggregated payment platform.

[0262] Optionally, the identity verification platform sends the identity verification result and credibility score to the aggregated payment platform.

[0263] Figure 4 This is a schematic diagram of the interface for the authentication result described in an embodiment of this application. Figure 4 The interface shown informs the user of the authentication result.

[0264] Therefore, the identity verification platform in this application integrates DIRT, DWMAS, and MIVM, realizing secure distributed storage and dynamic reconstruction of user identity information, adaptive weight adjustment based on real-time risk assessment, and multi-dimensional interactive verification. This comprehensive approach effectively solves the security risks of traditional centralized storage and the problem of slow response of static weight systems to risk changes. It significantly improves the security, privacy protection level, accuracy, and adaptability of identity verification in aggregated payment scenarios, and solves the security risks of existing aggregated payment methods, as well as the problems of insufficient security, weak privacy protection, and poor adaptability of existing aggregated payment identity verification technologies.

[0265] In this embodiment, DIRT, DWMAS, and MIVM are integrated to design a user authentication process in a highly secure and privacy-protected aggregated payment method. Once the user's authentication is successful, the user can continue with subsequent payment operations.

[0266] Please refer to Figure 5 This application also provides an aggregated payment method applied to an aggregated payment platform, the method comprising:

[0267] Step 501: After obtaining the user's authentication result sent by the authentication platform and sending the authentication result to the user, perform an irreversible transformation on the aggregated payment data sent by the user to obtain the transformed aggregated payment data.

[0268] It should be noted that the aggregated payment platform obtains the user's identity verification result sent by the identity verification platform, and then sends the identity verification result to the user, which includes whether the verification was successful or unsuccessful.

[0269] If the identity verification result is successful, the user sends aggregated payment data to the aggregated payment platform. This aggregated payment data is encrypted.

[0270] The identity verification result is obtained by the identity verification platform when a user initiates an aggregated payment request to the aggregated payment platform. Based on the user's identity information sent by the aggregated payment platform, the platform performs a multi-dimensional risk assessment on the user to obtain an initial risk score, and then performs multi-dimensional identity verification on the user based on the initial risk score.

[0271] Furthermore, the aggregated payment platform processes payments based on aggregated payment data to ensure the security, accuracy, and efficiency of payments.

[0272] In this embodiment of the application, the aggregated payment data may optionally include at least one of the following:

[0273] Transaction amount; payment method; payee information; transaction timestamp.

[0274] In one implementation method, optionally, the aggregated payment data sent by the user is irreversibly transformed to obtain transformed aggregated payment data, including:

[0275] The aggregated payment data is irreversibly transformed according to a predefined irreversible transformation function to obtain the transformed aggregated payment data. The irreversible transformation function includes at least one of secure hash operation, pseudo-random number generation operation, bitwise XOR operation, and cyclic shift operation.

[0276] Specifically, the aggregated payment data sent by the user undergoes an irreversible transformation to obtain transformed aggregated payment data, including:

[0277] Step a, Key generation: Generate a one-time key K based on the current timestamp and session ID.

[0278] K = H(timestamp||sess) i onid||salt)

[0279] Where H is a secure hash function; || represents string concatenation; salt is the preset salt value; timestamp is the timestamp; session i d is the session ID.

[0280] Step b, Data Transformation: Perform an irreversible transformation on the aggregated payment data D sent by the user to obtain the transformed aggregated payment data D′:

[0281] D′=T(D,K)

[0282] Where T is an irreversible transformation function, designed as follows:

[0283] T(D,K)=H(D||K)⊕D⊕PRNG(K)⊕ROT(D,H(K)[0:8])

[0284] in:

[0285] D represents the aggregated payment data sent by the user;

[0286] H(D||K) is a secure hash operation that uses SHA-256 to concatenate the aggregated payment data D sent by the user and the one-time key K into strings.

[0287] PRNG(K) represents the output of a pseudo-random number generator based on a one-time key K;

[0288] ⊕ indicates a bitwise XOR operation.

[0289] ROT(D,H(K)[0:8]) represents a cyclic bit shift operation based on the first 8 bits of the hash value of the one-time key K, defined as follows:

[0290] ROT(D,H(K)[0:8])=(D<<H(K)[0:8])|(D> >(|D|-H(K)[0:8]))

[0291] Where |D| represents the bit length of the aggregated payment data D sent by the user; << and >> represent left shift and right shift operations, respectively; and | represents a bitwise OR operation.

[0292] Step c, Integrity verification: Generate verification code V.

[0293] V=H(D′||K)

[0294] Step 502: Send the transformed aggregated payment data to the payment verification platform;

[0295] Optionally, the aggregated payment platform sends a data packet to the payment verification platform, which includes: the transformed aggregated payment data D′, the verification code V, and the session ID.

[0296] It should be noted that the aggregated payment platform adopts the Irreversible Data Transformation Transmission (IDTT) technology, which includes steps 501 and 502, to achieve secure transmission of aggregated payment data.

[0297] Considering the vulnerability of data transmission in aggregated payment environments to man-in-the-middle attacks and data tampering, and the shortcomings of existing encrypted transmission technologies such as complex key management and high computational overhead, this application adopts IDTT technology. This IDTT technology, through one-time key generation, irreversible transformation, and dynamic verification, achieves secure transmission and integrity verification of aggregated payment data, solving the security vulnerabilities and performance problems of traditional encryption methods, and significantly improving the system's security and transmission efficiency.

[0298] Step 503: Obtain the payment processing result sent by the payment verification platform;

[0299] The payment processing result includes success or failure.

[0300] Step 504: Send the payment processing result to the user.

[0301] Please refer to Figure 6 This application also provides an aggregated payment method applied to a payment verification platform, the method comprising:

[0302] Step 601: If the transformed aggregated payment data sent by the aggregated payment platform is obtained, the transformed aggregated payment data is restored to obtain the restored aggregated payment data.

[0303] In this embodiment of the application, the aggregated payment data is obtained by the aggregated payment platform after it receives the user's identity verification result from the identity verification platform and sends the identity verification result to the user. The identity verification result is obtained by the identity verification platform when the user initiates an aggregated payment request to the aggregated payment platform, based on the user's identity information sent by the aggregated payment platform, performing a multi-dimensional risk assessment on the user to obtain an initial risk score, and performing multi-dimensional identity verification on the user based on the initial risk score.

[0304] It should be noted that the payment verification platform uses IDTT technology, which includes step 601, to achieve secure transmission of aggregated payment data.

[0305] Optionally, the payment verification platform obtains the data packet sent by the aggregated payment platform, which includes: transformed aggregated payment data D′, verification code V and session ID, and then extracts the transformed aggregated payment data D′, verification code V and session ID from the data packet.

[0306] In one implementation, optionally, data recovery is performed on the transformed aggregated payment data to obtain recovered aggregated payment data, including:

[0307] The integrity of the transformed aggregated payment data is verified to obtain the integrity verification result;

[0308] If the integrity verification result is passed, the aggregated payment data of the transformation is restored according to the inverse operation of the predefined irreversible transformation function to obtain the restored aggregated payment data. The irreversible transformation function includes at least one of the following: secure hash operation, pseudo-random number generation operation, bitwise XOR operation, and cyclic shift operation.

[0309] Specifically, the integrity of the transformed aggregated payment data is verified to obtain the integrity verification result, including:

[0310] Regenerate the one-time key K using the session ID;

[0311] Data integrity verification: Generate a hash value based on the one-time key K and the transformed aggregated payment data D′. If the hash value is equal to the check code V, the data integrity verification passes.

[0312] Here is an example of code for data integrity verification:

[0313]

[0314] Specifically, data recovery is performed on the aggregated payment data transformed by the inverse operation of a predefined irreversible transformation function to obtain the recovered aggregated payment data, including:

[0315] D = T -1 (D′,K)=ROT -1 (D′⊕H(D′||K)⊕PRNG(K),H(K)[0:8])

[0316] Where D represents the recovered aggregated payment data;

[0317] D′ represents the transformed aggregated payment data;

[0318] K is a one-time key;

[0319] ROT -1 It is the inverse operation of ROT, defined as:

[0320] ROT-1 (X,n)=(X>>n)|(X<<(|X|-n))

[0321] Where X is the input of the ROT function, i.e., X = D′⊕H(D′||K)⊕PRNG(K);

[0322] |X| represents the bit length of X;

[0323] << and >> represent left shift and right shift operations, respectively;

[0324] | indicates a bitwise OR operation;

[0325] n is the displacement parameter, i.e., n = H(K)[0:8].

[0326] Step 602: Based on the recovered aggregated payment data, execute multi-dimensional payment verification rules to obtain payment verification results;

[0327] It should be noted that the payment verification platform adopts the Intelligent Verification Contract Execution Framework (IVCEF), including steps 602 to 603. It considers the diverse payment methods and complex payment verification rules in aggregated payment scenarios. Through smart contract technology, parallel processing, and dynamic rule engines, it achieves intelligent processing and efficient verification of payment requests, solving the problem that traditional payment systems struggle to adapt to diverse payment scenarios and greatly improving the flexibility and efficiency of payment processing. Specifically, it includes steps a to d in the following embodiments.

[0328] In one implementation method, optionally, multi-dimensional payment verification rules are executed based on the recovered aggregated payment data to obtain a payment verification result, including:

[0329] Based on the payment type in the recovered aggregated payment data, obtain multi-dimensional payment verification rules related to the payment type;

[0330] Based on the recovered aggregated payment data, obtain the verification function value corresponding to the payment verification rule for each dimension;

[0331] The payment verification result is obtained based on the verification function value corresponding to the payment verification rule for each dimension.

[0332] Here, the payment type is related to the payment client used, including but not limited to: WeChat Pay, Alipay, UnionPay, etc. Different payment types correspond to different multi-dimensional payment verification rules. These multi-dimensional payment verification rules can be referred to as smart contract templates.

[0333] Specifically, based on the recovered aggregated payment data, multi-dimensional payment verification rules are executed to obtain payment verification results, including:

[0334] Step a, Contract initialization: Select the corresponding multi-dimensional payment verification rule based on the payment type in the recovered aggregated payment data D.

[0335] Step b, rule loading: dynamically load multi-dimensional payment verification rules R.

[0336] Optionally, the multi-dimensional payment verification rules are predefined by the payment verification platform and include at least one of the following:

[0337] Basic transaction verification rules; payment method-specific rules; risk control rules; compliance rules; merchant-specific rules.

[0338] For example, the payment type is WeChat Pay, and the multi-dimensional payment verification rules R include the following R1 to R8:

[0339] Basic transaction verification rules:

[0340] R1: The transaction amount must be greater than 0 and not exceed the preset maximum limit, as shown in the following expression:

[0341] r1(amount) = (0 <amount≤MAX_AMOUNT)

[0342] R2: Transaction time must be within the time range allowed by the system, as shown in the following expression:

[0343]

[0344] Payment method specific rules:

[0345] R3: The daily cumulative transaction amount for WeChat Pay cannot exceed the limit, expressed as follows:

[0346] r3(amount,user_id)=(DAILY_SUM(amount,user_id,′WeChat′)+amount≤WECHAT_DAILY_LIMIT)

[0347] Risk control rules:

[0348] R4: Large transactions require additional authentication, as shown in the following expression:

[0349] r5(amount,extra_auth)=(amount <HIGH_AMOUNT_THRESHOLDORextra_auth=TRUE)

[0350] Compliance rules:

[0351] R5: Transactions must comply with anti-money laundering regulations, expressed as follows:

[0352] r7(amount,user_id)=(amount <AML_THRESHOLDORAML_CHECK(user_id,amount)=PASS)

[0353] R6: Cross-border payments must comply with foreign exchange control regulations, as shown below:

[0354] r8(currency,amount)=(currency=′CNY′ORFOREX_CHECK(amount,currency)=APPROVED)

[0355] Merchant-specific rules:

[0356] R7: The amount of a single transaction for a high-risk merchant must not exceed a specific limit, expressed as follows:

[0357] r9(amount,merchant_id)=(RISK_LEVEL(merchant_id)!='HIGH'ORamount≤HIGH_RISK_MERCHANT_LIMIT)

[0358] R8: New merchants have a special limit on their daily transaction volume, expressed as follows:

[0359] r10(amount,merchant_id)=(MERCHANT_AGE(merchant_id)>90ORDAILY_SUM(amount,merchant_id)≤NEW_MERCHANT_LIMIT) Step c, parallel verification: Apply the core verification function V in IVCEF, defined as follows:

[0360]

[0361] Where D represents the recovered aggregated payment data;

[0362] d i It is a single data item;

[0363] R stands for multi-dimensional payment verification rules;

[0364] r i It is a single-dimensional payment verification rule;

[0365] v i It is a single-item verification function, i.e., d i Does it conform to r?i If the condition is met, return 1; otherwise, return 0.

[0366] Step d, Decision Execution: If the result of the core verification function V is 1, then the decision logic in the smart contract is executed to obtain a payment verification result of 1, which indicates that the payment was successful; otherwise, it is not executed and a payment verification result of 0 is obtained, which indicates that the payment failed.

[0367] Step 603: Perform payment processing based on the payment verification result to obtain the payment processing result;

[0368] It should be noted that if the payment verification result is 1, indicating that the payment was successful, the actual payment operation will be executed, including fund transfer, account update, etc.

[0369] In this embodiment of the application, optionally, a transaction certificate (transaction success information) or transaction failure information is generated based on the payment processing result.

[0370] Optionally, payment processing results can be recorded on a distributed ledger to prevent modification. Furthermore, transaction information can be recorded on the distributed ledger to ensure transparency and immutability.

[0371] Figure 7 This is a flowchart illustrating a second implementation of the aggregated payment method described in this application; as follows: Figure 7 As shown, the method includes:

[0372] Step 701: Create a payment processing session and generate a unique session ID;

[0373] Step 702: The aggregated payment platform uses IDTT technology to transmit the transformed aggregated payment data to the payment verification platform;

[0374] Step 703: The payment verification platform receives the transformed aggregated payment data and performs integrity verification on the transformed aggregated payment data.

[0375] Step 704: Determine whether the integrity verification passed;

[0376] Step 705: Integrity verification passed, data recovery was performed on the transformed aggregated payment data to obtain the recovered aggregated payment data;

[0377] Step 706: The payment verification platform uses IVCEF to perform multi-dimensional payment verification based on the recovered aggregated payment data to obtain the payment verification result;

[0378] Step 707: Obtain the payment processing result;

[0379] Step 708: Record the payment processing result in the distributed ledger;

[0380] Step 709, integrity verification failed, error returned.

[0381] Optionally, a payment security status indicator can be used to inform the user of the payment processing result.

[0382] Figure 8 This is a schematic diagram of the interface for the payment processing result described in an embodiment of this application. Figure 8 The interface shown informs the user of the payment processing result.

[0383] Step 604: Send the payment processing result to the aggregated payment platform.

[0384] Furthermore, the aggregated payment platform returns the payment processing results to the user.

[0385] Therefore, the payment verification platform in this application integrates IDTT and IVCEF technologies to achieve secure transmission, efficient verification, and intelligent processing of aggregated payment data. This comprehensive approach effectively solves the problems of data leakage risks, low processing efficiency, and complex cross-platform payment verification in traditional payment systems. It significantly improves the security, efficiency, and adaptability of payment processing in aggregated payment scenarios, and addresses the issues of data transmission security risks, low payment verification efficiency, and poor cross-platform compatibility in existing aggregated payment methods.

[0386] Figure 9 This is a flowchart illustrating a third implementation of the aggregated payment method described in this application. Figure 9 As shown, the method includes:

[0387] Step 901: The user initiates an aggregated payment request to the aggregated payment platform;

[0388] Step 902: The aggregated payment platform sends user identity information to the identity verification platform, requesting user identity verification;

[0389] Step 903: The identity verification platform applies DIRT to reconstruct user identity information;

[0390] Step 904: The authentication platform uses DWMAS to perform multidimensional authentication;

[0391] Step 905: The authentication platform uses MIVM to obtain a trust score;

[0392] Step 906: The identity verification platform returns the identity verification result to the aggregated payment platform;

[0393] Step 907: The aggregated payment platform sends a verification message to the user and requests aggregated payment data;

[0394] Step 908: The user submits aggregated payment data to the aggregated payment platform;

[0395] Step 909: The aggregated payment platform uses IDTT technology to forward the transformed aggregated payment data to the payment verification platform;

[0396] Step 910: The payment verification platform uses IDTT to process the payment request;

[0397] Step 911: The payment verification platform uses IVCEF to obtain the payment processing result;

[0398] Step 912: The distributed ledger records the transaction;

[0399] Step 913, Distributed ledger confirmation record;

[0400] Step 914: The payment verification platform returns the payment processing result to the aggregated payment platform;

[0401] Step 915: The aggregated payment platform returns the payment processing result to the user.

[0402] In summary, this application provides an aggregated payment method, including DIRT, DWMAS, MIVM, IDTT technologies, and IVCEF. The integrated application of these technologies enables secure storage and dynamic reconstruction of user identity information, multi-dimensional interactive verification, secure transmission of aggregated payment data, and intelligent processing. Through these technologies, this application significantly improves the overall security, privacy protection level, processing efficiency, and cross-platform adaptability of the aggregated payment system, providing users with a safer and more efficient payment experience.

[0403] Please refer to Figure 10 This application also provides an aggregated payment device for use in an identity verification platform, the device comprising:

[0404] The risk assessment module 1001 is used to perform a multi-dimensional risk assessment on the user based on the user identity information sent by the aggregated payment platform when the user initiates an aggregated payment request to the aggregated payment platform, and obtain an initial risk score;

[0405] The identity verification module 1002 is used to perform multi-dimensional identity verification on the user based on the initial risk score and obtain the identity verification result;

[0406] The first sending module 1003 is used to send the identity verification result to the aggregated payment platform.

[0407] Optionally, in the aggregated payment device, the risk assessment module 1001 includes:

[0408] The reconstruction unit is used to reconstruct the user identity information sent by the aggregated payment platform to obtain the reconstructed user identity information;

[0409] An assessment unit is used to perform a multi-dimensional risk assessment on the user based on the reconstructed user identity information to obtain an initial risk score.

[0410] Optionally, in the aggregated payment device, the reconfiguration unit includes:

[0411] The encryption subunit is used to obtain an encrypted user identity fragment based on the user identity information sent by the aggregated payment platform;

[0412] The reconstruction subunit is used to reconstruct the user private key fragment in the user identity information based on the encrypted user identity fragment, and obtain the reconstructed user private key fragment;

[0413] The operation subunit is used to perform an XOR operation on the encrypted user identity fragment and the reconstructed user private key fragment to obtain the reconstructed user identity information.

[0414] Optionally, in the aforementioned aggregated payment device, the operation subunit is specifically used for:

[0415] Based on the reconstructed user private key fragment, the encrypted user identity fragment is decrypted to obtain the decrypted user identity fragment;

[0416] Perform an XOR operation on multiple decrypted user identity fragments to obtain the first user identity information;

[0417] An XOR operation is performed on the first user identity information and the first hash function value to obtain the reconstructed user identity information. The first hash function value is obtained based on the user's unique identifier in the user identity information.

[0418] Optionally, in the aforementioned aggregated payment device, the evaluation unit is specifically used for:

[0419] Based on the reconstructed user identity information, user transaction characteristics are obtained;

[0420] For predefined multi-dimensional risk factors, a score for each risk factor is obtained based on the user transaction characteristics corresponding to each risk factor.

[0421] An initial risk score is obtained based on the time interval since the last successful authentication, the predefined impact coefficient, the time-sensitive item coefficient, the maximum timeout threshold, and the weight and score of each risk factor.

[0422] Optionally, in the aforementioned aggregated payment device, the identity verification module 1002 is specifically used for:

[0423] For predefined multi-dimensional authentication, the dynamic weight of each authentication dimension is obtained based on the initial risk score;

[0424] A score for each dimension of authentication is obtained based on the dynamic weight of each dimension of authentication.

[0425] The authentication result is obtained based on the score for each dimension of authentication and the user's aggregated payment characteristic score.

[0426] It should be noted that the apparatus provided in this application embodiment can implement all the method steps implemented in the above-mentioned method embodiment applied to the identity verification platform, and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.

[0427] Please refer to Figure 11 This application also provides an aggregated payment device for use on an aggregated payment platform, the device comprising:

[0428] The transformation module 1101 is used to irreversibly transform the aggregated payment data sent by the user when the user's authentication result is obtained from the authentication platform and the authentication result is sent to the user, so as to obtain the transformed aggregated payment data.

[0429] The second sending module 1102 is used to send the transformed aggregated payment data to the payment verification platform;

[0430] The first acquisition module 1103 is used to acquire the payment processing result sent by the payment verification platform;

[0431] The third sending module 1104 is used to send the payment processing result to the user.

[0432] Optionally, in the aforementioned aggregated payment device, the conversion module 1101 is specifically used for:

[0433] The aggregated payment data sent by the user is irreversibly transformed according to a predefined irreversible transformation function to obtain the transformed aggregated payment data. The irreversible transformation function includes at least one of secure hash operation, pseudo-random number generation operation, bitwise XOR operation, and cyclic shift operation.

[0434] It should be noted that the apparatus provided in this application embodiment can implement all the method steps implemented in the above-mentioned method embodiment applied to the aggregated payment platform, and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.

[0435] Please refer to Figure 12 This application also provides an aggregated payment device for use in a payment verification platform, the device comprising:

[0436] The recovery module 1201 is used to recover the transformed aggregated payment data sent by the aggregated payment platform when the transformed aggregated payment data is obtained, so as to obtain the recovered aggregated payment data.

[0437] The payment verification module 1202 is used to perform multi-dimensional payment verification based on the recovered aggregated payment data and obtain the payment verification result;

[0438] The second acquisition module 1203 is used to perform payment processing based on the payment verification result and acquire the payment processing result.

[0439] The fourth sending module 1204 is used to send the payment processing result to the aggregated payment platform.

[0440] Optionally, in the aforementioned aggregated payment device, the recovery module 1201 is specifically used for:

[0441] The integrity of the transformed aggregated payment data is verified to obtain the integrity verification result;

[0442] If the integrity verification result is passed, the aggregated payment data of the transformation is restored according to the inverse operation of the predefined irreversible transformation function to obtain the restored aggregated payment data. The irreversible transformation function includes at least one of the following: secure hash operation, pseudo-random number generation operation, bitwise XOR operation, and cyclic shift operation.

[0443] Optionally, in the aforementioned aggregated payment device, the payment verification module 1202 is specifically used for:

[0444] Based on the payment type in the recovered aggregated payment data, obtain multi-dimensional payment verification rules related to the payment type;

[0445] Based on the recovered aggregated payment data, obtain the verification function value corresponding to the payment verification rule for each dimension;

[0446] The payment verification result is obtained based on the verification function value corresponding to the payment verification rule for each dimension.

[0447] It should be noted that the apparatus provided in this application embodiment can implement all the method steps implemented in the above-mentioned method embodiment applied to the payment verification platform, and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.

[0448] This application also provides an aggregated payment device, such as... Figure 13 As shown, it includes:

[0449] The processor 1301, memory 1302, transceiver 1303, and programs or instructions stored in the memory 1302 and executable on the processor 1301; when the processor 1301 executes the programs or instructions, it implements the various processes of the above-described aggregated payment method embodiments and achieves the same technical effect. To avoid repetition, these will not be described again here.

[0450] The transceiver 1303 is used to receive and send data under the control of the processor 1301.

[0451] Among them, Figure 13 In this context, the bus architecture can include any number of interconnected buses and bridges, specifically connecting various circuits of one or more processors represented by processor 1301 and memory represented by memory 1302. The bus architecture can also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. The bus interface provides an interface. The transceiver 1303 can be multiple elements, including transmitters and receivers, providing a unit for communicating with various other devices over a transmission medium. For different user equipment, the user interface 1304 can also be an interface capable of connecting external or internal devices, including but not limited to keypads, displays, speakers, microphones, joysticks, etc.

[0452] The processor 1301 is responsible for managing the bus architecture and general processing, while the memory 1302 can store the data used by the processor 1301 when performing operations.

[0453] This application also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the various processes of the above-described aggregated payment method embodiments and achieves the same technical effects. To avoid repetition, it will not be described again here. The computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0454] This application also provides a computer program product, including computer instructions. When the computer instructions are executed by a processor, they implement the various processes of the above-described aggregated payment method embodiments and achieve the same technical effects. To avoid repetition, they will not be described again here.

[0455] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0456] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0457] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A method for aggregated payment, characterized in that, Applied to an authentication platform, the method includes: When a user initiates an aggregated payment request to the aggregated payment platform, a multi-dimensional risk assessment is performed on the user based on the user identity information sent by the aggregated payment platform to obtain an initial risk score; Based on the initial risk score, multi-dimensional identity verification is performed on the user to obtain the identity verification result; Send the identity verification result to the aggregated payment platform.

2. The aggregated payment method according to claim 1, characterized in that, Based on the user identity information sent by the aggregated payment platform, a multi-dimensional risk assessment is performed on the user to obtain an initial risk score, including: The user identity information sent by the aggregated payment platform is reconstructed to obtain the reconstructed user identity information; Based on the reconstructed user identity information, a multi-dimensional risk assessment is performed on the user to obtain an initial risk score.

3. The aggregated payment method according to claim 2, characterized in that, The user identity information sent by the aggregated payment platform is reconstructed to obtain the reconstructed user identity information, including: Based on the user identity information sent by the aggregated payment platform, an encrypted user identity fragment is obtained; The user private key fragment in the user identity information is reconstructed based on the encrypted user identity fragment to obtain the reconstructed user private key fragment. The reconstructed user identity information is obtained by performing an XOR operation on the encrypted user identity fragment and the reconstructed user private key fragment.

4. The aggregated payment method according to claim 3, characterized in that, Perform an XOR operation on the encrypted user identity fragment and the reconstructed user private key fragment to obtain the reconstructed user identity information, including: Based on the reconstructed user private key fragment, the encrypted user identity fragment is decrypted to obtain the decrypted user identity fragment; Perform an XOR operation on multiple decrypted user identity fragments to obtain the first user identity information; An XOR operation is performed on the first user identity information and the first hash function value to obtain the reconstructed user identity information. The first hash function value is obtained based on the user's unique identifier in the user identity information.

5. The aggregated payment method according to claim 2, characterized in that, Based on the reconstructed user identity information, a multi-dimensional risk assessment is performed on the user to obtain an initial risk score, including: Based on the reconstructed user identity information, user transaction characteristics are obtained; For predefined multi-dimensional risk factors, a score for each risk factor is obtained based on the user's trading characteristics corresponding to each risk factor. An initial risk score is obtained based on the time interval since the last successful authentication, the predefined impact coefficient, the time-sensitive item coefficient, the maximum timeout threshold, and the weight and score of each risk factor.

6. The aggregated payment method according to claim 1, characterized in that, Based on the initial risk score, multi-dimensional authentication is performed on the user to obtain authentication results, including: For predefined multi-dimensional authentication, the dynamic weight of each authentication dimension is obtained based on the initial risk score; A score for each dimension of authentication is obtained based on the dynamic weight of each dimension of authentication. The authentication result is obtained based on the score for each dimension of authentication and the user's aggregated payment characteristic score.

7. A method for aggregated payment, characterized in that, Applied to aggregated payment platforms, the method includes: Upon obtaining the user's authentication result from the authentication platform and sending the authentication result to the user, the aggregated payment data sent by the user is irreversibly transformed to obtain the transformed aggregated payment data. Send the transformed aggregated payment data to the payment verification platform; Obtain the payment processing result sent by the payment verification platform; The payment processing result is sent to the user.

8. The aggregated payment method according to claim 7, characterized in that, The aggregated payment data sent by the user is irreversibly transformed to obtain transformed aggregated payment data, including: The aggregated payment data sent by the user is irreversibly transformed according to a predefined irreversible transformation function to obtain the transformed aggregated payment data. The irreversible transformation function includes at least one of secure hash operation, pseudo-random number generation operation, bitwise XOR operation, and cyclic shift operation.

9. A method for aggregated payment, characterized in that, Applied to a payment verification platform, the method includes: Upon receiving the transformed aggregated payment data sent by the aggregated payment platform, the transformed aggregated payment data is recovered to obtain the recovered aggregated payment data. Based on the recovered aggregated payment data, perform multi-dimensional payment verification to obtain the payment verification result; Based on the payment verification result, the payment is processed to obtain the payment processing result; The payment processing result is sent to the aggregated payment platform.

10. The aggregated payment method according to claim 9, characterized in that, Data recovery is performed on the transformed aggregated payment data to obtain the recovered aggregated payment data, including: The integrity of the transformed aggregated payment data is verified to obtain the integrity verification result; If the integrity verification result is passed, the aggregated payment data of the transformation is restored according to the inverse operation of the predefined irreversible transformation function to obtain the restored aggregated payment data. The irreversible transformation function includes at least one of the following: secure hash operation, pseudo-random number generation operation, bitwise XOR operation, and cyclic shift operation.

11. The aggregated payment method according to claim 9, characterized in that, Based on the recovered aggregated payment data, multi-dimensional payment verification is performed to obtain payment verification results, including: Based on the payment type in the recovered aggregated payment data, obtain multi-dimensional payment verification rules related to the payment type; Based on the recovered aggregated payment data, obtain the verification function value corresponding to the payment verification rule for each dimension; The payment verification result is obtained based on the verification function value corresponding to the payment verification rule for each dimension.

12. A payment aggregation device, characterized in that, The device, used in an authentication platform, includes: The risk assessment module is used to perform a multi-dimensional risk assessment on the user based on the user identity information sent by the aggregated payment platform when the user initiates an aggregated payment request to the aggregated payment platform, and obtain an initial risk score; An identity verification module is used to perform multi-dimensional identity verification on the user based on the initial risk score and obtain an identity verification result; The first sending module is used to send the identity verification result to the aggregated payment platform.

13. A payment aggregation device, characterized in that, The device, used in an aggregated payment platform, includes: The transformation module is used to irreversibly transform the aggregated payment data sent by the user when the user's authentication result is obtained from the authentication platform and the authentication result is sent to the user, so as to obtain the transformed aggregated payment data. The second sending module is used to send the transformed aggregated payment data to the payment verification platform; The first acquisition module is used to acquire the payment processing result sent by the payment verification platform; The third sending module is used to send the payment processing result to the user.

14. A payment aggregation device, characterized in that, The device, used in a payment verification platform, includes: The recovery module is used to recover the transformed aggregated payment data sent by the aggregated payment platform when the transformed aggregated payment data is obtained, so as to obtain the recovered aggregated payment data. The payment verification module is used to perform multi-dimensional payment verification based on the recovered aggregated payment data and obtain the payment verification result; The second acquisition module is used to perform payment processing based on the payment verification result and acquire the payment processing result. The fourth sending module is used to send the payment processing result to the aggregated payment platform.

15. An aggregated payment device, characterized in that, include: A processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the processor, when executing the program or instructions, implements the aggregated payment method as described in any one of claims 1 to 6, or implements the aggregated payment method as described in any one of claims 7 to 8, or implements the aggregated payment method as described in any one of claims 9 to 11.

16. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the aggregated payment method as described in any one of claims 1 to 6, or the aggregated payment method as described in any one of claims 7 to 8, or the aggregated payment method as described in any one of claims 9 to 11.

17. A computer program product, characterized in that, It includes computer instructions, which, when executed by a processor, implement the aggregated payment method as described in any one of claims 1 to 6, or the aggregated payment method as described in any one of claims 7 to 8, or the aggregated payment method as described in any one of claims 9 to 11.

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