Secure transaction service terminal based on AI cloud platform

Abstract

The present invention discloses a secure transaction service terminal based on an AI cloud platform, including: a publishing module, used to publish the transaction services that can be provided to the user end through multiple AI cloud platforms, as well as the types, functions, usage requirements and charging standards of the transaction services provided; a first determination module, used to obtain the demand information fed back by the user end, and determine the target AI cloud platform from multiple AI cloud platforms according to the demand information; an establishment module, used to establish a secure link between the user end and the target AI cloud platform, and the target AI cloud platform provides secure transaction services for the user end. According to the demand information of the user end, the corresponding AI cloud platform is matched, transaction loopholes and transaction risks in the transaction process are prevented, and corresponding secure transaction services are provided to the user to improve security.

Description

Technical Field

[0001] The present invention relates to the technical field of transaction services, and in particular to a secure transaction service terminal based on an AI cloud platform. Background Art

[0002] At present, cloud computing provides users with a large number of virtual and dynamically scalable resources through the Internet, such as computing resources, storage resources, hardware platforms, and applications, which provides great flexibility and convenience for transactions between users and cloud servers. However, cloud computing and cloud storage have serious security issues, especially for users who frequently trade with cloud servers. For example, when users use outsourced storage services of cloud servers, data privacy becomes a major issue, including security issues such as illegal users accessing cloud server resources to steal legitimate users' data and "phishing" caused by legitimate users accessing illegal servers.

[0003] Different user ends have different demand information. Using multiple AI cloud platforms with single resource specifications will lead to waste or shortage of resources. It is impossible to match the corresponding AI cloud platform according to the demand information. There are transaction loopholes and transaction risks in the transaction process, and it is impossible to achieve secure transaction services. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems in the above-mentioned technology to a certain extent. To this end, the purpose of the present invention is to propose a secure transaction service terminal based on an AI cloud platform, match the corresponding AI cloud platform according to the demand information of the user end, prevent transaction loopholes and transaction risks in the transaction process, provide users with corresponding secure transaction services, and improve security.

[0005] To achieve the above objectives, the embodiment of the present invention proposes a secure transaction service terminal based on an AI cloud platform, comprising:

[0006] The publishing module is used to publish the transaction services it can provide to the user end through multiple AI cloud platforms, as well as the types, functions, usage requirements and charging standards of the transaction services provided;

[0007] A first determination module is used to obtain demand information fed back by a user, and determine a target AI cloud platform from multiple AI cloud platforms according to the demand information;

[0008] A module is established to establish a secure link between the user terminal and the target AI cloud platform, and the target AI cloud platform provides secure transaction services for the user terminal.

[0009] According to some embodiments of the present invention, the publishing module includes:

[0010] The description module is used to determine the types of transaction services provided by each AI cloud platform and to provide a functional description of each transaction service;

[0011] The first formulation module is used to formulate usage requirements according to the technical characteristics and application scenarios of the transaction service; the usage requirements include the technical capabilities, hardware configuration and network environment that the user terminal needs to have;

[0012] The second formulation module is used to formulate charging standards based on service costs, market demand and competition, and provide multiple billing methods; billing methods include pay-as-you-go, subscription, and annual package services.

[0013] According to some embodiments of the present invention, the terminal further includes: an identity authentication module, configured to:

[0014] Before the module establishes a secure link between the user and the target AI cloud platform, obtain the identity information of the user;

[0015] Preprocessing identity information;

[0016]

[0017] in, For identity information Information Preprocessed data; is the mean of identity information, is the precise coefficient, and its value range is (0,1);

[0018] Calculate the similarity between the identity information and the preset identity information in the target AI cloud platform;

[0019]

[0020] in, The similarity between the identity information and the preset identity information in the target AI cloud platform; The preset identity information Data of individual information; is the number of information contained in the preset identity information, and is also the number of information contained in the identity information;

[0021] The similarity between the identity information and the preset identity information in the target AI cloud platform is compared with the preset similarity threshold. When it is determined that the similarity is greater than or equal to the preset similarity threshold, it means that the identity information verification of the user end has passed; otherwise, it means that the identity information verification of the user end has failed; the establishment module establishes a secure link between the user end whose identity information has passed the verification and the target AI cloud platform.

[0022] According to some embodiments of the present invention, the terminal further includes: a first identification module, configured to:

[0023] In the process of the target AI cloud platform providing secure transaction services to the user end, determine the transaction service control flow chart, perform a global scan of the transaction service control flow chart, and locate the data interaction instructions therein;

[0024] Determine the risk nodes in the transaction scenario according to the data interaction instructions, and determine the risk type of each risk node; connect the risk data generated by the risk nodes of the same risk type into a chain according to the order in which the transactions occurred to obtain a transaction risk data chain, and obtain several transaction risk data chains according to the risk nodes of different risk types;

[0025] Extract risk-related data from each transaction risk data chain to form multiple risk data sets, each of which contains different risk characteristics;

[0026] According to the risk types corresponding to the transaction risk data chains and the different risk characteristics corresponding to the multiple risk data sets, the multiple risk data sets are mapped into multiple mapping spaces based on a machine learning algorithm, and each risk data set corresponds to one mapping space; views are generated in the mapping space according to the window parameters, and the generated views are spliced ​​into a transaction risk sequence diagram, thereby determining the transaction risk sequence diagram corresponding to each transaction risk data chain;

[0027] Connect several transaction risk sequence diagrams based on the order in which the transactions occurred to obtain a target transaction risk sequence diagram;

[0028] According to the target transaction risk sequence diagram, each target risk node and potential risk mode are identified, and corresponding blocking measures are formulated; wherein, the blocking measures include strengthening identity authentication, limiting transaction amount, and setting transaction rules.

[0029] According to some embodiments of the present invention, the terminal further includes: a blocking module, configured to:

[0030] Count the risk level and risk duration of each target risk node;

[0031] Determine the blocking priority of each target risk node based on the risk level and risk duration;

[0032] According to the blocking priority of each target risk node, corresponding blocking measures are formulated in turn, and blocking actions are executed.

[0033] According to some embodiments of the present invention, the terminal further includes: a second determining module, configured to:

[0034] Determine the risk level of the target transaction risk sequence diagram and mark it;

[0035] When it is determined that the risk level of the target transaction risk sequence diagram is greater than the preset risk level, an alarm prompt is issued.

[0036] According to some embodiments of the present invention, the second determining module includes:

[0037] The first calculation module is used to calculate the probability of anomaly at the i-th risk node in the target transaction risk sequence diagram :

[0038]

[0039] in, is a combined symbol; The number of risk nodes included in the target transaction risk sequence graph; The maximum classification error rate when distinguishing the risk category of the risk node when judging whether an abnormality occurs in the risk node;

[0040] The second calculation module is used to calculate the risk level of the target transaction risk sequence diagram according to the probability of an abnormality occurring at the i-th risk node in the target transaction risk sequence diagram :

[0041]

[0042] in, The total number of risk categories of risk nodes included in the target transaction risk sequence diagram; The coverage area of ​​the target transaction risk sequence diagram; To determine the difference between the risk category of the i-th risk node and the actual risk category.

[0043] According to some embodiments of the present invention, the terminal further includes: a second identification module, configured to:

[0044] Determine transaction information during the process of the target AI cloud platform providing secure transaction services to the user end;

[0045] Conduct sensitive identification of transaction information and determine sensitive and non-sensitive data;

[0046] Encrypt sensitive data to obtain encrypted data;

[0047] Modified transaction information is obtained based on the encrypted data and the non-sensitive data, and a secure transaction service is performed based on the modified transaction information.

[0048] According to some embodiments of the present invention, the second identification module performs sensitivity identification on the transaction information to determine sensitive data and non-sensitive data, including:

[0049] Establish a set of identification rules for sensitive data; the identification rule set includes: one or more sensitive data types and their identification rules; the identification rules are implemented using regular expressions, and different sensitive data types have different rule strategies;

[0050] According to the identification rule set, the transaction information is scanned for sensitive identification to determine sensitive data and non-sensitive data.

[0051] The present invention proposes a secure transaction service terminal based on an AI cloud platform, which matches the corresponding AI cloud platform according to the demand information of the user end, prevents transaction loopholes and transaction risks in the transaction process, provides users with corresponding secure transaction services, and improves security.

[0052] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0053] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0055] Figure 1 is a block diagram of a secure transaction service terminal based on an AI cloud platform according to an embodiment of the present invention;

[0056] Figure 2 is a block diagram of a publishing module according to an embodiment of the present invention;

[0057] Figure 3 It is a block diagram of a secure transaction service terminal based on an AI cloud platform according to yet another embodiment of the present invention. DETAILED DESCRIPTION

[0058] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0059] like Figure 1 As shown, the embodiment of the present invention proposes a secure transaction service terminal based on an AI cloud platform, including:

[0060] The publishing module is used to publish the transaction services it can provide to the user end through multiple AI cloud platforms, as well as the types, functions, usage requirements and charging standards of the transaction services provided;

[0061] A first determination module is used to obtain demand information fed back by a user, and determine a target AI cloud platform from multiple AI cloud platforms according to the demand information;

[0062] A module is established to establish a secure link between the user terminal and the target AI cloud platform, and the target AI cloud platform provides secure transaction services for the user terminal.

[0063] The working principle of the above technical solution is: the publishing module is responsible for publishing transaction service information to the user end through multiple AI cloud platforms. This information includes but is not limited to the types of transaction services (such as commodity transactions, service transactions, etc.), functional characteristics, usage requirements (such as whether specific software and hardware support are required, etc.) and charging standards (such as one-time fees, pay-per-use, subscription, etc.). Using technical means such as API interfaces and Web services, service information is pushed to each AI cloud platform in the form of structured data.

[0064] The first determination module is responsible for receiving demand information fed back by the user end, and determining the target AI cloud platform from multiple AI cloud platforms based on this information. Demand information includes the type of transaction expected by the user, service quality requirements, budget constraints, etc. A machine learning algorithm is used to intelligently analyze and match user needs. By comparing the service characteristics of each AI cloud platform and the degree of matching of user needs, the target AI cloud platform is determined from multiple AI cloud platforms. The establishment module is responsible for establishing a secure link between the user end and the target AI cloud platform to ensure the security and privacy protection of the transaction process. The secure link uses encrypted communication protocols (such as HTTPS, TLS, etc.) to prevent data leakage and tampering.

[0065] The beneficial effects of the above technical solution are: matching the corresponding AI cloud platform according to the user's demand information, preventing transaction loopholes and transaction risks in the transaction process, providing users with corresponding secure transaction services, and improving security.

[0066] like Figure 2 As shown, according to some embodiments of the present invention, the publishing module includes:

[0067] The description module is used to determine the types of transaction services provided by each AI cloud platform and to provide a functional description of each transaction service;

[0068] The first formulation module is used to formulate usage requirements according to the technical characteristics and application scenarios of the transaction service; the usage requirements include the technical capabilities, hardware configuration and network environment that the user terminal needs to have;

[0069] The second formulation module is used to formulate charging standards based on service costs, market demand and competition, and provide multiple billing methods; billing methods include pay-as-you-go, subscription, and annual package services.

[0070] Working principle and beneficial effects of the above technical solution: The description module is responsible for determining the types of transaction services provided by each AI cloud platform and providing a detailed functional description of each transaction service. Service information is displayed in a variety of forms such as text, images, and videos so that users can understand the functional characteristics, usage scenarios, and potential value of each service. The first formulation module formulates detailed usage requirements based on the technical characteristics and application scenarios of the transaction service. These requirements include the technical capabilities that the user side needs to have (such as software version, programming interface support, etc.), hardware configuration (such as processor performance, memory size, etc.) and network environment (such as bandwidth, latency, etc.). The second formulation module formulates charging standards based on service costs, market demand, and competition, and provides a variety of billing methods for users to choose from. These billing methods include volume-based billing (such as billing based on the number of transactions, data volume, etc.), subscription system (such as monthly, quarterly, annual, etc. subscription services), annual package services, etc. The publishing module realizes the comprehensive publication and meticulous management of transaction service information by introducing the description module, the first formulation module, and the second formulation module. These modules work together to provide users with clear, accurate, and actionable transaction service information, and provide users with a variety of options to meet their actual needs. At the same time, these modules also provide effective service management and marketing means for the AI ​​cloud platform.

[0071] like Figure 3 As shown, according to some embodiments of the present invention, the terminal further includes: an identity authentication module, configured to:

[0072] Before the module establishes a secure link between the user and the target AI cloud platform, obtain the identity information of the user;

[0073] Preprocessing identity information;

[0074]

[0075] in, For identity information Information Preprocessed data; is the mean of identity information, is the precise coefficient, and its value range is (0,1);

[0076] Calculate the similarity between the identity information and the preset identity information in the target AI cloud platform;

[0077]

[0078] in, The similarity between the identity information and the preset identity information in the target AI cloud platform; The preset identity information Data of individual information; is the number of information contained in the preset identity information, and is also the number of information contained in the identity information;

[0079] The similarity between the identity information and the preset identity information in the target AI cloud platform is compared with the preset similarity threshold. When it is determined that the similarity is greater than or equal to the preset similarity threshold, it means that the identity information verification of the user end has passed; otherwise, it means that the identity information verification of the user end has failed; the establishment module establishes a secure link between the user end whose identity information has passed the verification and the target AI cloud platform.

[0080] The working principle and beneficial effects of the above technical solution: Before the module establishes a secure link, the identity authentication module first obtains the identity information of the user end. This information includes user name, password, biometric data (such as fingerprint, facial recognition data), and device information (such as MAC address, IP address). The acquired identity information will undergo a preprocessing step to improve the accuracy and efficiency of subsequent similarity calculations. Among them, α is the mean of the identity information, and τ is the precision coefficient, which is used to adjust the accuracy of the preprocessing. The formula combines the ideas of mean centering and standardization, and introduces an precision coefficient to fine-tune the results. The preprocessed identity information will be similarity calculated with the preset identity information in the target AI cloud platform. The preset identity information is the identity information of a legitimate user. This formula combines the ideas of vector dot product and cubic root to emphasize the importance of certain information or reduce the impact of noise. The calculated similarity will be compared with the preset similarity threshold. If the similarity is greater than or equal to the preset threshold, it means that the identity information of the user end has been verified; otherwise, it means that the verification has not been passed. The user end that has passed the identity authentication will be allowed to establish a secure link with the target AI cloud platform for subsequent transaction services. The identity authentication module is an important part of ensuring the security of secure transaction service terminals based on AI cloud platforms. Through reasonable preprocessing, accurate similarity calculation and strict verification process, this module can effectively prevent unauthorized users from accessing the target AI cloud platform and ensure the security and reliability of transaction services.

[0081] According to some embodiments of the present invention, the terminal further includes: a first identification module, configured to:

[0082] In the process of the target AI cloud platform providing secure transaction services to the user end, determine the transaction service control flow chart, perform a global scan of the transaction service control flow chart, and locate the data interaction instructions therein;

[0083] Determine the risk nodes in the transaction scenario according to the data interaction instructions, and determine the risk type of each risk node; connect the risk data generated by the risk nodes of the same risk type into a chain according to the order in which the transactions occurred to obtain a transaction risk data chain, and obtain several transaction risk data chains according to the risk nodes of different risk types;

[0084] Extract risk-related data from each transaction risk data chain to form multiple risk data sets, each of which contains different risk characteristics;

[0085] According to the risk types corresponding to the transaction risk data chains and the different risk characteristics corresponding to the multiple risk data sets, the multiple risk data sets are mapped into multiple mapping spaces based on a machine learning algorithm, and each risk data set corresponds to one mapping space; views are generated in the mapping space according to the window parameters, and the generated views are spliced ​​into a transaction risk sequence diagram, thereby determining the transaction risk sequence diagram corresponding to each transaction risk data chain;

[0086] Connect several transaction risk sequence diagrams based on the order in which the transactions occurred to obtain a target transaction risk sequence diagram;

[0087] According to the target transaction risk sequence diagram, each target risk node and potential risk mode are identified, and corresponding blocking measures are formulated; wherein, the blocking measures include strengthening identity authentication, limiting transaction amount, and setting transaction rules.

[0088] The working principle and beneficial effects of the above technical solution: During the process of transaction service, the first identification module first determines the control flow chart of the transaction service. This flow chart describes the entire process of the transaction service from the beginning to the end, including various steps, conditional branches and decision points. The control flow chart is globally scanned to locate the data interaction instructions therein. These instructions are the key nodes and key data of the data flow in the transaction process.

[0089] According to the data interaction instructions, the module determines the risk nodes in the transaction scenario. Risk nodes are links or operations that may cause risks. For each risk node, the module further determines its risk type, such as fraud risk, credit risk, operational risk, etc. For risk nodes of the same risk type, the module connects the risk data it generates into a chain according to the order in which the transactions occurred, forming a transaction risk data chain. According to risk nodes of different risk types, the module obtains several transaction risk data chains.

[0090] The transaction risk data chain contains data records of each link in the transaction process, such as transaction time, transaction amount, information of both parties to the transaction, transaction type, etc. On the basis of parsing the data chain, data directly related to the risk is screened out. These data include abnormal transaction behavior, suspicious capital flow, illegal operation records, etc. For the screened risk-related data, its risk characteristics are further extracted. Risk characteristics refer to data indicators that can reflect the nature and characteristics of risks, such as transaction frequency, transaction amount fluctuations, counterparty reputation, etc. Based on the extracted risk characteristics, multiple risk data sets are constructed. Each risk data set contains different risk feature combinations, which can comprehensively reflect different aspects of transaction risks. Extracting risk-related data from each transaction risk data chain and forming multiple risk data sets are key steps in the risk management process. By constructing an accurate and comprehensive risk data set and combining it with advanced algorithms and technical means, accurate identification, evaluation and monitoring of transaction risks can be achieved.

[0091] Matching is performed based on the risk type corresponding to the transaction risk data chain and the different risk characteristics corresponding to multiple risk data sets. This means that each risk data set is closely related to its corresponding risk type and contains specific characteristics of the risk type. Machine learning algorithms (such as clustering algorithms, classification algorithms, or dimensionality reduction algorithms, etc.) are applied to map multiple risk data sets into multiple mapping spaces. These mapping spaces can be two-dimensional, three-dimensional, or even higher-dimensional spaces, depending on the complexity of the data and the capabilities of the algorithm. For each risk data set, an independent mapping space is assigned to it. In this way, each space focuses on displaying the data characteristics and risk trends of its corresponding risk type. In each mapping space, views are generated based on window parameters (such as zoom, viewing angle, color mapping, etc.). These parameters determine how the view displays the data, including the density, distribution, trend, etc. of the data. Based on the set window parameters, views are generated in each mapping space. These views can be scatter plots, heat maps, line graphs, etc., depending on the type of data and the information to be displayed. The generated views are spliced ​​together according to a certain logic or order to form a transaction risk sequence diagram. This sequence diagram shows the evolution and distribution of risks throughout the entire process from the beginning to the end of the transaction. The transaction risk sequence diagram is interactive, allowing users to view data at different time points and different risk types through operations such as zooming, panning, and clicking. At the same time, it should be able to be dynamically updated to reflect the latest transaction data and risk status. By mapping multiple sets of risk data sets into multiple mapping spaces, generating views in these spaces and splicing them into a transaction risk sequence diagram, comprehensive, intuitive, and dynamic management of transaction risks can be achieved. This approach not only improves the efficiency of risk management, but also enhances the accuracy of decision-making.

[0092] Ensure that each transaction risk sequence diagram contains timestamp or timeline information so that it can be spliced ​​in the order in which the transactions occurred. Align the timeline to ensure that each sequence diagram is continuous in time, without missing or repeated time periods. Splice each transaction risk sequence diagram in chronological order to form a complete target transaction risk sequence diagram. In the target transaction risk sequence diagram, determine the risk value of each risk node based on the application of statistical methods, and screen out risk nodes with risk values ​​greater than the risk threshold by comparing with the risk threshold to identify each target risk node. These nodes include abnormal points, mutation points or high-risk areas in the transaction process. Analyze the transaction data around the target risk node to identify potential risk methods or patterns. These methods include fraudulent behavior, illegal transactions, etc. For identified high-risk transactions or users, strengthen identity authentication measures, such as adding verification steps, using biometric technology, etc. Set a transaction amount cap for specific transactions or users to reduce potential losses and risks. The amount limit can be adjusted according to the risk level and user credibility. Formulate or adjust transaction rules to limit the occurrence of high-risk transactions or behaviors. For example, certain types of transactions can be restricted to a specific time period, or users can be required to provide additional information to complete the transaction. By splicing multiple transaction risk sequence diagrams into a target transaction risk sequence diagram, and identifying risk nodes and potential risk methods based on this sequence diagram, and finally formulating corresponding blocking measures, transaction risks can be effectively reduced and risk management levels can be improved, making it easier to achieve safe transaction services.

[0093] According to some embodiments of the present invention, the terminal further includes: a blocking module, configured to:

[0094] Count the risk level and risk duration of each target risk node;

[0095] Determine the blocking priority of each target risk node based on the risk level and risk duration;

[0096] According to the blocking priority of each target risk node, corresponding blocking measures are formulated in turn, and blocking actions are executed.

[0097] The working principle and beneficial effects of the above technical solution: The blocking module first counts the risk level of each target risk node. The risk level is usually obtained by comprehensive evaluation based on factors such as the possibility of risk occurrence, the degree of impact, and historical data, and can be divided into different levels such as high, medium, and low. The risk duration of each risk node is recorded, that is, the time from the risk being identified to the current moment. The risk duration helps to assess the persistence and urgency of the risk. According to the risk level and risk duration, the blocking module will formulate a blocking priority list. Generally, risk nodes with higher risk levels and longer risk durations will be given higher blocking priorities. For risk nodes with high risks and long durations, blocking measures should be taken first to prevent further expansion of risks. To ensure the reasonable allocation and efficient use of resources. According to the blocking priority list, the blocking module will formulate corresponding blocking measures in turn. Once the blocking measures are determined, the module will immediately execute the blocking action to cut off the propagation path of the risk node and prevent the risk from further spreading. After executing the blocking measures, the blocking module will continue to monitor the state changes of the risk nodes to ensure the effectiveness of the blocking measures. If it is found that the blocking measures fail to achieve the expected effect or new changes occur in the risk nodes, the module will adjust the blocking strategy in time and re-execute the blocking action. The blocking module is an important part of the risk management process. It determines the blocking priority by statistically analyzing the risk level and risk duration, and formulates corresponding blocking measures to execute the blocking action. By continuously optimizing and improving the blocking strategy, the module will be able to provide users with safer and more reliable trading services.

[0098] According to some embodiments of the present invention, the terminal further includes: a second determining module, configured to:

[0099] Determine the risk level of the target transaction risk sequence diagram and mark it;

[0100] When it is determined that the risk level of the target transaction risk sequence diagram is greater than the preset risk level, an alarm prompt is issued.

[0101] The working principle and beneficial effects of the above technical solution: Evaluate the risk level of the target transaction risk sequence diagram and divide the risk into different levels, such as low, medium, high or a specific numerical range (such as 1-10). Update the marked risk level information to the target transaction risk sequence diagram for subsequent analysis and monitoring. According to business needs and security requirements, set one or more preset risk levels, which can be used as thresholds for triggering alarms. Monitor the target transaction risk sequence diagram in real time or regularly, and pay attention to changes in risk levels. When it is found that the risk level in the target transaction risk sequence diagram is greater than the preset risk level, the alarm mechanism is triggered. The risk level of the target transaction risk sequence diagram can be effectively determined, and whether the transaction is safe can be evaluated from the overall transaction service process, and an alarm prompt can be issued when necessary, thereby ensuring the security and stability of the transaction.

[0102] According to some embodiments of the present invention, the second determining module includes:

[0103] The first calculation module is used to calculate the probability of anomaly at the i-th risk node in the target transaction risk sequence diagram :

[0104]

[0105] in, is a combined symbol; The number of risk nodes included in the target transaction risk sequence graph; The maximum classification error rate when distinguishing the risk category of the risk node when judging whether an abnormality occurs in the risk node;

[0106] The second calculation module is used to calculate the risk level of the target transaction risk sequence diagram according to the probability of an abnormality occurring at the i-th risk node in the target transaction risk sequence diagram :

[0107]

[0108] in, The total number of risk categories of risk nodes included in the target transaction risk sequence diagram; The coverage area of ​​the target transaction risk sequence diagram; To determine the difference between the risk category of the i-th risk node and the actual risk category.

[0109] The working principle and beneficial effects of the above technical solution: C is a combination symbol, which indicates a combination method of selecting i risk nodes from m risk nodes. λ is the maximum classification error rate when distinguishing the risk category of the risk node when judging whether an abnormality occurs in the risk node, indicating the accuracy of the system in classifying the risk node. It is a quantitative value that represents the scope or scale of transactions covered by the target transaction risk series diagram. is a quantitative value indicating the degree of classification error. The formula in the first calculation module is a probability calculation formula based on binomial distribution, which is used to calculate the probability of abnormality at each risk node. The formula in the second calculation module is a comprehensive evaluation formula that takes into account multiple factors such as the number of risk nodes, abnormal probability, risk category differences, and the coverage area of ​​the risk sequence diagram. The calculated risk level W can be used to evaluate the overall risk status of the target transaction risk sequence diagram and serve as a basis for formulating risk management strategies. Through the synergy of the first calculation module and the second calculation module, the risk level of the target transaction risk sequence diagram can be accurately calculated, providing strong support for risk management.

[0110] According to some embodiments of the present invention, the terminal further includes: a second identification module, configured to:

[0111] Determine transaction information during the process of the target AI cloud platform providing secure transaction services to the user end;

[0112] Conduct sensitive identification of transaction information and determine sensitive and non-sensitive data;

[0113] Encrypt sensitive data to obtain encrypted data;

[0114] Modified transaction information is obtained based on the encrypted data and the non-sensitive data, and a secure transaction service is performed based on the modified transaction information.

[0115] The working principle and beneficial effects of the above technical solution: in the process of the target AI cloud platform providing secure transaction services to the user end, the transaction information is determined; sensitive identification is performed on the transaction information to determine sensitive data and non-sensitive data;

[0116] Encrypt sensitive data to obtain encrypted data; the purpose of encryption is to ensure the security of sensitive data during transmission and storage, and to prevent unauthorized access and leakage. Encryption methods include symmetric encryption, asymmetric encryption, etc.

[0117] The modified transaction information is obtained based on the encrypted data and non-sensitive data, and the secure transaction service is performed based on the modified transaction information. The modified transaction information can still support the normal transaction while ensuring security. The second identification module ensures the confidentiality and integrity of sensitive data and prevents data leakage or tampering by sensitive identification and processing of transaction information.

[0118] According to some embodiments of the present invention, the second identification module performs sensitivity identification on the transaction information to determine sensitive data and non-sensitive data, including:

[0119] Establish a set of identification rules for sensitive data; the identification rule set includes: one or more sensitive data types and their identification rules; the identification rules are implemented using regular expressions, and different sensitive data types have different rule strategies;

[0120] According to the identification rule set, the transaction information is scanned for sensitive identification to determine sensitive data and non-sensitive data.

[0121] The working principle and beneficial effects of the above technical solution: The second identification module first establishes a set of identification rules for sensitive data. This rule set is the basis for sensitive identification. It contains various sensitive data types that appear in transaction information and their corresponding identification rules. Sensitive data types include but are not limited to: user identity information (such as name, ID number, mobile phone number), bank account information (such as account number, password, verification code), transaction amount, geographic location information, etc. For each sensitive data type, corresponding identification rules are set. These rules are implemented using regular expressions, which are a powerful text processing tool that can match strings that conform to specific patterns. Different sensitive data types have different rule strategies. For example, for mobile phone numbers, regular expressions can be used to match 11-digit strings that start with specific numbers; for ID numbers, regular expressions can be used to match strings that conform to the format of Chinese ID numbers. According to the established identification rule set, the second identification module starts scanning transaction information. During the scanning process, the module will try to match each field or string with the rules in the identification rule set. If a field or string successfully matches the identification rule of a sensitive data type, then the field or string is considered sensitive data. The second identification module can determine which data is sensitive data and which is non-sensitive data. Sensitive data needs to be encrypted to ensure its security, while non-sensitive data can be used directly for transaction services. The second identification module can accurately determine the sensitive data and non-sensitive data in the transaction information by establishing a set of identification rules for sensitive data and using regular expressions for sensitive identification, thus providing security for transaction services.

[0122] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A secure transaction service terminal based on an AI cloud platform, characterized in that: include: The publishing module is used to publish the transaction services it can provide to the user end through multiple AI cloud platforms, as well as the types, functions, usage requirements and charging standards of the transaction services provided; A first determination module is used to obtain demand information fed back by a user, and determine a target AI cloud platform from multiple AI cloud platforms according to the demand information; Establish a module for establishing a secure link between the user end and the target AI cloud platform, and the target AI cloud platform provides secure transaction services for the user end; The terminal further includes: a first identification module, configured to: In the process of the target AI cloud platform providing secure transaction services to the user end, determine the transaction service control flow chart, perform a global scan on the transaction service control flow chart, and locate the data interaction instructions therein; Determine the risk nodes in the transaction scenario according to the data interaction instructions, and determine the risk type of each risk node; connect the risk data generated by the risk nodes of the same risk type into a chain according to the order in which the transactions occurred to obtain a transaction risk data chain, and obtain several transaction risk data chains according to the risk nodes of different risk types; Extract risk-related data from each transaction risk data chain to form multiple risk data sets, each of which contains different risk characteristics; According to the risk types corresponding to the transaction risk data chains and the different risk characteristics corresponding to the multiple risk data sets, the multiple risk data sets are mapped into multiple mapping spaces based on a machine learning algorithm, and each risk data set corresponds to one mapping space; views are generated in the mapping space according to the window parameters, and the generated views are spliced ​​into a transaction risk sequence diagram, thereby determining the transaction risk sequence diagram corresponding to each transaction risk data chain; Connect several transaction risk sequence diagrams based on the order in which the transactions occurred to obtain a target transaction risk sequence diagram; According to the target transaction risk sequence diagram, each target risk node and potential risk mode are identified, and corresponding blocking measures are formulated; wherein, the blocking measures include strengthening identity authentication, limiting transaction amount, and setting transaction rules.

2. The AI ​​cloud platform-based secure transaction service terminal according to claim 1, characterized in that: The publishing module comprises: The description module is used to determine the types of transaction services provided by each AI cloud platform and to provide a functional description of each transaction service; The first formulation module is used to formulate usage requirements according to the technical characteristics and application scenarios of the transaction service; the usage requirements include the technical capabilities, hardware configuration and network environment that the user terminal needs to have; The second formulation module is used to formulate charging standards based on service costs, market demand and competition, and provide multiple billing methods; billing methods include pay-as-you-go, subscription, and annual package services.

3. The secure transaction service terminal based on the AI ​​cloud platform according to claim 1, characterized in that: The terminal also includes an identity verification module for: Before the module establishes a secure link between the user and the target AI cloud platform, obtain the identity information of the user; Preprocessing identity information; in, For identity information Information Preprocessed data; is the mean of identity information, is the precise coefficient, and its value range is (0,1); Calculate the similarity between the identity information and the preset identity information in the target AI cloud platform; in, The similarity between the identity information and the preset identity information in the target AI cloud platform; The preset identity information Data of individual information; is the number of information contained in the preset identity information, and is also the number of information contained in the identity information; The similarity between the identity information and the preset identity information in the target AI cloud platform is compared with the preset similarity threshold. When it is determined that the similarity is greater than or equal to the preset similarity threshold, it means that the identity information verification of the user end has passed; otherwise, it means that the identity information verification of the user end has failed; the establishment module establishes a secure link between the user end whose identity information has passed the verification and the target AI cloud platform.

4. The secure transaction service terminal based on the AI ​​cloud platform according to claim 1, characterized in that: The terminal further includes a blocking module, configured to: Count the risk level and risk duration of each target risk node; Determine the blocking priority of each target risk node based on the risk level and risk duration; According to the blocking priority of each target risk node, corresponding blocking measures are formulated in turn, and blocking actions are executed.

5. The secure transaction service terminal based on the AI ​​cloud platform according to claim 1, characterized in that: The terminal further includes: a second determining module, configured to: Determine the risk level of the target transaction risk sequence diagram and mark it; When it is determined that the risk level of the target transaction risk sequence diagram is greater than the preset risk level, an alarm prompt is issued.

6. The AI ​​cloud platform-based secure transaction service terminal according to claim 5, characterized in that: The second determining module includes: The first calculation module is used to calculate the probability of anomaly at the i-th risk node in the target transaction risk sequence diagram : in, is a combined symbol; The number of risk nodes included in the target transaction risk sequence graph; The maximum classification error rate when distinguishing the risk category of the risk node when judging whether an abnormality occurs in the risk node; The second calculation module is used to calculate the risk level of the target transaction risk sequence diagram according to the probability of an abnormality occurring at the i-th risk node in the target transaction risk sequence diagram : in, The total number of risk categories of risk nodes included in the target transaction risk sequence diagram; The coverage area of ​​the target transaction risk sequence diagram; To determine the difference between the risk category of the i-th risk node and the actual risk category.

7. The secure transaction service terminal based on the AI ​​cloud platform according to claim 1, characterized in that: The terminal further includes: a second identification module, configured to: Determine transaction information during the process of the target AI cloud platform providing secure transaction services to the user end; Conduct sensitive identification of transaction information and determine sensitive and non-sensitive data; Encrypt sensitive data to obtain encrypted data; Modified transaction information is obtained based on the encrypted data and the non-sensitive data, and a secure transaction service is performed based on the modified transaction information.

8. The AI ​​cloud platform-based secure transaction service terminal according to claim 7, characterized in that: The second identification module performs sensitive identification on the transaction information to determine sensitive data and non-sensitive data, including: Establish a set of identification rules for sensitive data; the identification rule set includes: one or more sensitive data types and their identification rules; the identification rules are implemented using regular expressions, and different sensitive data types have different rule strategies; According to the identification rule set, the transaction information is scanned for sensitive identification to determine sensitive data and non-sensitive data.

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