Payment security evaluation system suitable for network merchant service platform

Abstract

The invention belongs to the field of payment security assessment, relates to a data analysis technology, and is used for solving the problem that an existing payment security assessment system cannot effectively identify payment security in combination with payment business and payment network data during payment, in particular to a payment security assessment system suitable for a network merchant service platform. Comprising a payment security evaluation center which is in communication connection with a payment service analysis end and a payment network analysis end. The payment service analysis end comprises a payment service monitoring module, a user management module and a payment service evaluation module; the payment network analysis end comprises a payment network monitoring module and a payment network evaluation module; the payment service behavior of the user is analyzed through the payment service analysis end, the network environment condition is analyzed through the payment network analysis end, the payment safety is graded through the payment safety evaluation center in combination with the payment service and the payment network, and it is guaranteed that the payment safety level can be accurately evaluated and the payment risk can be coped with.

Description

Technical Field

[0001] The present invention belongs to the field of payment security assessment, relates to data analysis technology, and specifically is a payment security assessment system applicable to an online merchant service platform. Background Art

[0002] With the rapid development of e-commerce and online payment, online merchant service platforms play an increasingly important role in modern business; however, the accompanying payment security issues have become increasingly prominent; online merchant service platforms face various payment risks, including but not limited to fraudulent transactions, illegal access, data leakage, etc.; these security issues not only threaten the financial security and privacy information of users, but also seriously affect the reputation and sustainable development of online merchant service platforms.

[0003] To solve these problems, an effective payment security assessment system is needed to monitor and analyze payment operations and network environments in real time, and timely detect and respond to potential security threats; currently, although there are some payment security assessment tools and technologies in the market, they usually focus on single-aspect security assessment, such as data encrypted transmission, user behavior characteristics, etc., and often cannot effectively identify payment security by combining payment operation data and payment network data during the payment process, nor can they comprehensively evaluate the payment security level, resulting in the inability to accurately prevent payment risks for different payment security levels.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the Invention

[0005] The purpose of the present invention is to provide a payment security assessment system applicable to an online merchant service platform, which is used to solve the problem that the existing payment security assessment system applicable to an online merchant service platform cannot effectively identify payment security by combining payment operation data and payment network data during the payment process; The technical problem that the present invention needs to solve is: how to provide a payment security assessment system applicable to an online merchant service platform that can effectively identify payment security by combining payment operation data and payment network data during the payment process.

[0006] The purpose of the present invention can be achieved through the following technical solutions: A payment security assessment system applicable to an online merchant service platform includes a payment security assessment center, and the payment security assessment center is communicatively connected to a payment operation analysis terminal and a payment network analysis terminal; the payment operation analysis terminal includes a payment operation monitoring module, a user management module, and a payment operation assessment module; the payment network analysis terminal includes a payment network monitoring module and a payment network assessment module; The payment service monitoring module is used to monitor the transaction behaviors in the online merchant service platform: generate a monitoring period of a fixed duration, and obtain a payment coefficient ZF by analyzing the payment services of users within the monitoring period; The user management module is used to classify and manage the users in the online merchant service platform: classify users into normal users, suspicious users, and abnormal users based on the payment coefficient; The payment service evaluation module is used to evaluate the payment services in the online merchant service platform: obtain the number of normal users ZC, the number of suspicious users KY, and the number of abnormal users YC in the online merchant service platform within the monitoring period, and generate a payment service qualified or unqualified signal by analyzing the number of normal users ZC, the number of suspicious users KY, and the number of abnormal users YC; The payment network monitoring module is used to monitor the payment network environment of the online merchant service platform: obtain the network traffic LL and the average bandwidth utilization rate DK of the online merchant service platform within the monitoring period, and calculate a network coefficient WX based on the network traffic LL and the average bandwidth utilization rate DK; The payment network judgment module is used to evaluate the payment network of the online merchant service platform: generate a payment network qualified signal or unqualified signal by judging the network coefficient WX; The payment security evaluation center is used to comprehensively evaluate the payment security by combining the payment services and the payment network conditions: evaluate the payment security level of the online merchant service platform through the payment service signal and the payment network signal.

[0007] Further, the process of obtaining the payment coefficient ZF includes: generating a monitoring period with a fixed duration of T, obtaining the number of transactions JC of the user for online transactions within the monitoring period, the payment amount ZJ, the payment time, and the payment location for each transaction, and through the formula obtain the payment coefficient ZF of the user, where w is the location correction factor and t is the time correction factor.

[0008] Further, the value determination process of the location correction factor w is: if the payment location of the user for online transactions within the monitoring period changes, then w = 1; if the payment location of the user for online transactions within the monitoring period does not change, then w = 0.75.

[0009] Further, the value determination process of the time correction factor t is: extract the hour number of the payment time when the user conducts the transaction; calculate the variance of all the hour numbers within the monitoring time to obtain the hour number deviation value SP, and compare the hour number deviation value SP with the preset hour number deviation threshold SPmax: if the hour number deviation value SP is greater than or equal to the hour number deviation threshold SPmax, then t = 1; if the hour number deviation value SP is less than the hour number deviation threshold SPmax, then t = 0.75.

[0010] Further, the specific process of classifying and managing users includes: comparing the payment coefficient ZF of the user with a preset payment threshold ZFmax: if the payment coefficient ZF is greater than or equal to the payment threshold ZFmax, then determine that the user is a suspicious user; if the payment coefficient ZF is less than the payment threshold ZFmax, then determine that the user is a normal user; obtain the page stay time YT of the suspicious user when conducting transactions on the online merchant service platform; the process of obtaining the page stay time YT includes: marking the IP address of the suspicious user as a suspicious IP, obtaining the time intervals for the suspicious IP to jump between different pages through the back-end server of the online merchant service platform, summing up and averaging the time intervals of all page jumps of the same suspicious IP within the monitoring time period to obtain the page stay time YT of the abnormal user; comparing the page stay time YT of the suspicious user with a preset page stay time threshold YTmax: if the page stay time YT is less than or equal to the page stay time threshold YTmax, then mark the suspicious user as an abnormal user.

[0011] Further, the specific process of judging the payment service signal includes: obtaining the number of normal users ZC, the number of suspicious users KY, and the number of abnormal users YC in the online merchant service platform within the monitoring period; if KY / (ZC + KY) ≤ p and YC / KY ≤ q, then judge that the payment service of the online merchant service platform within the monitoring period meets the requirements, generate a qualified payment service signal and send the signal to the payment security evaluation center; if KY / (ZC + KY) > p and YC / KY > q, then judge that the payment service of the online merchant service platform within the monitoring period does not meet the requirements, generate an unqualified payment service signal and send the signal to the payment security evaluation center, where p and q are both ratio thresholds set by the management personnel themselves.

[0012] Further, the process of obtaining the network coefficient WX includes: obtaining the network traffic LL and the average bandwidth utilization rate DK of the online merchant service platform within the monitoring period; performing numerical calculations on the network traffic LL, the average bandwidth utilization rate DK, the number of normal users ZC, and the number of suspicious users KY to obtain the network coefficient WX of the online merchant service platform within the monitoring period.

[0013] Further, the specific process of judging the payment network signal includes: comparing the network coefficient WX with a preset network threshold WXmax. If the network coefficient WX is less than the network threshold WXmax, it is determined that the payment network environment of the network merchant service platform meets the requirements during the monitoring period, a payment network qualified signal is generated and sent to the payment security assessment center. If the network coefficient WX is greater than or equal to the network threshold WXmax, it is determined that the payment network environment of the network merchant service platform does not meet the requirements during the monitoring period, a payment network unqualified signal is generated and sent to the payment security assessment center.

[0014] Further, the specific process of evaluating the payment security level includes: if the payment service signal is qualified and the payment network signal is qualified, it is determined that the payment security level of the network merchant service platform is level one; if only one of the payment service signal and the payment network signal is unqualified, it is determined that the payment security level of the network merchant service platform is level two; if the payment service signal is unqualified and the payment network signal is unqualified, it is determined that the payment security level of the network merchant service platform is level three. The payment security assessment center sends the payment security level to the mobile terminal of the network merchant service platform management personnel.

[0015] The present invention has the following beneficial effects: Through the payment service monitoring module, the payment data on the network merchant service platform can be monitored in real time, and the payment coefficient can be corrected according to the user's payment behavior. This real-time nature ensures that abnormal transactions can be discovered in a timely manner, and the correction of the payment coefficient ensures the accuracy of data processing, providing data support for the classified management of users. By using the user management module to mark suspicious users and abnormal users, it is convenient for the network merchant service platform to conduct further analysis of user payment behavior, improving the efficiency of payment service evaluation. Through the payment network monitoring module, the network traffic and bandwidth utilization rate can be monitored and analyzed in real time, and the health status of the payment network environment can be evaluated, which helps to discover network attacks and traffic anomalies in a timely manner. 4. By combining the analysis of payment services and payment networks, the payment security level of the network merchant service platform can be comprehensively judged, which helps to more accurately identify and respond to payment risks. Description of the Drawings

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0017] Figure 1 This is the system block diagram of the whole invention. Detailed implementation manners

[0018] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0019] As Figure 1 shown, a payment security evaluation system applicable to an online merchant service platform includes a payment security evaluation center, which is communicatively connected to a payment service analysis end and a payment network analysis end; the payment service analysis end includes a payment service monitoring module, a user management module, and a payment service evaluation module; the payment network analysis end includes a payment network monitoring module and a payment network evaluation module.

[0020] Payment service analysis end: The payment service monitoring module is used to monitor the transaction behaviors in the online merchant service platform: generate a monitoring period with a fixed duration of T, obtain the number of transactions JC of the user in the monitoring period for online transactions, the payment amount ZJ, payment time, and payment location for each transaction; Through the formula the payment coefficient ZF of the user is obtained. In particular, the payment coefficient ZF represents the average intensity of the user's payment behavior through the online merchant service platform in the monitoring period. The higher the payment coefficient ZF, the higher the average intensity of the user's payment behavior through the online merchant service platform in the monitoring period; where w is the location correction factor and t is the time correction factor; The value determination process of the location correction factor w is as follows: If the payment location of the user for online transactions changes during the monitoring period, then w = 1; If the payment location of the user for online transactions does not change during the monitoring period, then w = 0.75; The value determination process of the time correction factor t is as follows: extract the hour number of the payment time when the user conducts the transaction. For example, if the user conducts a transaction at 19:52, then the hour number is 19; calculate the variance of all the hour numbers during the monitoring time to obtain the hour number deviation value SP, and compare the hour number deviation value SP with the preset hour number deviation threshold SPmax: If the hour number deviation value SP is greater than or equal to the hour number deviation threshold SPmax, then t = 1; If the hour number deviation value SP is less than the hour number deviation threshold SPmax, then t = 0.75; The payment business monitoring module can monitor the payment data on the online merchant service platform in real time and can correct the payment coefficient according to the user's payment behavior. This real-time feature ensures that abnormal transactions can be detected in a timely manner, and the correction of the payment coefficient ensures the accuracy of data processing, providing data support for the classification management of users.

[0021] The user management module is used to classify and manage the users in the online merchant service platform: compare the payment coefficient ZF of the user with the preset payment threshold ZFmax. If the payment coefficient ZF is greater than or equal to the payment threshold ZFmax, then determine that the user is a suspicious user; if the payment coefficient ZF is less than the payment threshold ZFmax, then determine that the user is a normal user. Obtain the page stay time YT of the suspicious user when conducting transactions on the online merchant service platform. The process of obtaining the page stay time YT includes: marking the IP address of the suspicious user as a suspicious IP, obtaining the time intervals for the suspicious IP to jump between different pages through the background server of the online merchant service platform, summing up and averaging all the page jump time intervals of the same suspicious IP within the monitoring time to obtain the page stay time YT of the abnormal user; compare the page stay time YT of the suspicious user with the preset page stay time threshold YTmax. If the page stay time YT is less than or equal to the page stay time threshold YTmax, then mark the suspicious user as an abnormal user. The payment business evaluation module is used to evaluate the payment business of the online merchant service platform: obtain the number of normal users ZC, the number of suspicious users KY, and the number of abnormal users YC in the online merchant service platform within the monitoring period. If KY / (ZC + KY) ≤ p and YC / KY ≤ q, then determine that the payment business of the online merchant service platform meets the requirements within the monitoring period, generate a qualified payment business signal and send the signal to the payment security evaluation center; if KY / (ZC + KY) > p and YC / KY > q, then determine that the payment business of the online merchant service platform does not meet the requirements within the monitoring period, generate an unqualified payment business signal and send the signal to the payment security evaluation center, where p and q are both ratio thresholds set by the management personnel themselves; mark the suspicious users and abnormal users through the user management module, which is convenient for the online merchant service platform to conduct further analysis of user payment behavior and improves the efficiency of payment business evaluation.

[0022] Payment network analysis end: The payment network monitoring module is used to monitor the payment network environment of the online merchant service platform: obtain the network traffic LL and the average bandwidth utilization rate DK of the online merchant service platform during the monitoring period; among them, the network traffic is the total amount of data transmitted through the network during the monitoring period, and the bandwidth utilization rate is the ratio of the actually used bandwidth to the total bandwidth at a certain moment, both of which can be obtained by analyzing the logs of the background server of the online merchant service platform; through the formula Perform numerical calculations on the network traffic LL, the average bandwidth utilization rate DK, the number of normal users ZC, and the number of suspicious users KY to obtain the network coefficient WX of the online merchant service platform during the monitoring period, where k1 and k2 are both proportionality coefficients; through the payment network monitoring module, real-time monitoring and analysis of the network traffic and bandwidth utilization rate can be carried out to evaluate the health status of the payment network environment, which helps to detect network attacks and traffic anomalies in a timely manner.

[0023] The payment network judgment module is used to evaluate the payment network of the online merchant service platform: compare the network coefficient WX with the preset network threshold WXmax: if the network coefficient WX is less than the network threshold WXmax, it is judged that the payment network environment of the online merchant service platform meets the requirements during the monitoring period, generate a payment network qualified signal and send the signal to the payment security evaluation center; if the network coefficient WX is greater than or equal to the network threshold WXmax, it is judged that the payment network environment of the online merchant service platform does not meet the requirements during the monitoring period, generate a payment network unqualified signal and send the signal to the payment security evaluation center; The payment security evaluation center is used to comprehensively evaluate payment security by combining the payment business and the status of the payment network: comprehensively evaluate the payment security of the online merchant service platform through the received payment business signal and payment network signal: if the payment business signal is qualified and the payment network signal is qualified, it is judged that the payment security level of the online merchant service platform is the first level; if only one of the payment business signal and the payment network signal is unqualified, it is judged that the payment security level of the online merchant service platform is the second level; if the payment business signal is unqualified and the payment network signal is unqualified, it is judged that the payment security level of the online merchant service platform is the third level; the payment security evaluation center sends the payment security level to the mobile terminal of the administrator of the online merchant service platform; by combining the analysis of the payment business and the payment network, the payment security level of the online merchant service platform can be comprehensively judged, which helps to more accurately identify and respond to payment risks.

[0024] A payment security evaluation system applicable to the service platform of online merchants. When working, it generates a monitoring period at the payment business analysis end, obtains the number of user transactions, payment amounts, payment times, and payment points within the monitoring period, and calculates and corrects to obtain a payment coefficient. The user management module determines suspicious users based on the payment coefficient and marks users with abnormal page stay times as abnormal users. The payment business evaluation module generates a qualified or unqualified signal for the payment business based on the number of normal users, suspicious users, and abnormal users. The payment network analysis end obtains a network coefficient by monitoring network traffic and the average bandwidth usage rate, and generates a qualified or unqualified signal for the payment network based on the network coefficient. The payment security evaluation center classifies the payment security level of the online merchant service platform into first level, second level, and third level based on the signals of the payment business and the payment network, and sends the payment security level to the mobile terminal of the management personnel.

[0025] The above content is only an example and illustration of the structure of the present invention. Those skilled in the art of this technology can make various modifications or supplements to the described specific embodiments or use similar methods to replace them. As long as they do not deviate from the structure of the invention or exceed the scope defined by this claim book, they should fall within the protection scope of the present invention.

[0026] The above formulas are all obtained by collecting a large amount of data for software simulation and selecting a formula close to the true value. The coefficients in the formulas are set by those skilled in the art according to the actual situation; for example: formula ; Those skilled in the art collect multiple groups of sample data and set corresponding network coefficients for each group of sample data; substitute the set network coefficients and the collected sample data into the formula. Any two formulas form a system of binary linear equations, screen the calculated coefficients and take the average value to obtain the values of k1 and k2 as 3.54 and 3.29 respectively; The magnitude of the coefficient is a specific value obtained by quantifying each parameter for subsequent comparison. Regarding the magnitude of the coefficient, it depends on the amount of sample data and the network coefficients initially set by those skilled in the art for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantified value, such as the network coefficient is proportional to the value of network traffic.

[0027] In the description of this specification, the description referring to terms such as "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0028] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only the specific embodiments. Obviously, many modifications and variations can be made according to the content of this specification. These embodiments are selected and specifically described in this specification in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A payment security assessment system applicable to an online merchant service platform, characterized in that: It includes a payment security assessment center, which is communicatively connected to a payment service analysis terminal and a payment network analysis terminal; the payment service analysis terminal includes a payment service monitoring module, a user management module and a payment service assessment module; the payment network analysis terminal includes a payment network monitoring module and a payment network assessment module; The payment service monitoring module is used to monitor the transaction behavior in the online merchant service platform: generate a monitoring period of fixed length, and obtain the payment coefficient ZF by analyzing the payment service of the user within the monitoring period; The user management module is used to classify and manage users in the online merchant service platform: users are classified into normal users, suspicious users and abnormal users according to payment coefficients; The payment service evaluation module is used to evaluate the payment service of the network merchant service platform: obtain the number of normal users ZC, the number of suspicious users KY and the number of abnormal users YC in the network merchant service platform within the monitoring period, and generate a payment service qualified or unqualified signal by analyzing the number of normal users ZC, the number of suspicious users KY and the number of abnormal users YC; The payment network monitoring module is used to monitor the payment network environment of the network merchant service platform: obtain the network traffic LL and the average bandwidth usage rate DK of the network merchant service platform during the monitoring period, and calculate the network coefficient WX according to the network traffic LL and the average bandwidth usage rate DK; The payment network judgment module is used to evaluate the payment network of the online merchant service platform: by judging the network coefficient WX, a payment network qualified signal or unqualified signal is generated; The payment security assessment center is used to conduct a comprehensive assessment of payment security in combination with the status of payment services and payment networks: the payment security of the online merchant service platform is assessed by payment service signals and payment network signals.

2. A payment security assessment system applicable to an online merchant service platform according to claim 1, characterized in that: The process of obtaining the payment coefficient ZF includes: generating a monitoring period with a fixed duration of T, obtaining the number of transactions JC of the user's online transactions during the monitoring period, the payment amount ZJ, payment time and payment location of each transaction, and calculating the payment coefficient ZF through the formula The user's payment coefficient ZF is obtained, where w is the location correction factor and t is the time correction factor.

3. A payment security assessment system applicable to an online merchant service platform according to claim 1, characterized in that: The value determination process of the location correction factor w is as follows: if the payment location for the user's online transaction changes during the monitoring period, then w=1; if the payment location for the user's online transaction does not change during the monitoring period, then w=0.

75.

4. A payment security assessment system applicable to an online merchant service platform according to claim 1, characterized in that: The value determination process of the time correction factor t is as follows: extract the payment time of the user's transaction; calculate the variance of all the hours within the monitoring time to obtain the hour deviation value SP, and compare the hour deviation value SP with the preset hour deviation threshold SPmax: if the hour deviation value SP is greater than or equal to the hour deviation threshold SPmax, then t=1; if the hour deviation value SP is less than the hour deviation threshold SPmax, then t=0.

75.

5. A payment security assessment system applicable to an online merchant service platform according to claim 1, characterized in that: The specific process of classifying and managing users includes: comparing the user's payment coefficient ZF with a preset payment threshold ZFmax: if the payment coefficient ZF is greater than or equal to the payment threshold ZFmax, the user is judged to be a suspicious user; if the payment coefficient ZF is less than the payment threshold ZFmax, the user is judged to be a normal user; obtaining the page residence time YT of the suspicious user when conducting transactions on the online merchant service platform; the process of obtaining the page residence time YT includes: marking the IP address of the suspicious user as a suspicious IP, obtaining the time interval for the suspicious IP to jump to different pages through the background server of the online merchant service platform, summing and averaging the time intervals of all page jumps of the same suspicious IP within the monitoring time, and obtaining the page residence time YT of the abnormal user; comparing the page residence time YT of the suspicious user with a preset page residence time threshold YTmax: if the page residence time YT is less than or equal to the page residence time threshold YTmax, the suspicious user is marked as an abnormal user.

6. A payment security assessment system applicable to an online merchant service platform according to claim 1, characterized in that: The specific process of judging the payment business signal includes: obtaining the number of normal users ZC, the number of suspicious users KY and the number of abnormal users YC in the network merchant service platform during the monitoring period; if KY / (ZC+KY)≤p and YC / KY≤q, then it is judged that the payment business of the network merchant service platform during the monitoring period meets the requirements, a payment business qualification signal is generated and the signal is sent to the payment security assessment center; if KY / (ZC+KY)>p and YC / KY>q, then it is judged that the payment business of the network merchant service platform during the monitoring period does not meet the requirements, a payment business failure signal is generated and the signal is sent to the payment security assessment center, where p and q are both proportion thresholds set by the management personnel.

7. A payment security assessment system applicable to an online merchant service platform according to claim 1, characterized in that: The process of obtaining the network coefficient WX includes: obtaining the network traffic LL and the average bandwidth usage rate DK of the network merchant service platform during the monitoring period; performing numerical calculations on the network traffic LL, the average bandwidth usage rate DK, the number of normal users ZC, and the number of suspicious users KY to obtain the network coefficient WX of the network merchant service platform during the monitoring period.

8. A payment security assessment system applicable to an online merchant service platform according to claim 1, characterized in that: The specific process of judging the payment network signal includes: comparing the network coefficient WX with the preset network threshold WXmax: if the network coefficient WX is less than the network threshold WXmax, it is judged that the payment network environment of the network merchant service platform during the monitoring period meets the requirements, and a payment network qualification signal is generated and sent to the payment security assessment center; if the network coefficient WX is greater than or equal to the network threshold WXmax, it is judged that the payment network environment of the network merchant service platform during the monitoring period does not meet the requirements, a payment network failure signal is generated and sent to the payment security assessment center.

9. A payment security assessment system applicable to an online merchant service platform according to claim 1, characterized in that: The specific process of evaluating the payment security level includes: if the payment business signal is qualified and the payment network signal is qualified, then the payment security level of the network merchant service platform is judged to be level one; if only one of the payment business signal and the payment network signal is unqualified, then the payment security level of the network merchant service platform is judged to be level two; if the payment business signal is unqualified and the payment network signal is unqualified, then the payment security level of the network merchant service platform is judged to be level three; the payment security assessment center sends the payment security level to the mobile terminal of the network merchant service platform manager.

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