Method and device for processing transaction data, processor and computing equipment

Abstract

The invention relates to a method and device for processing transaction data, a processor and computing equipment. The method comprises the following steps: responding to a transaction object, performing transaction by scanning a two-dimensional code, and obtaining transaction data, the transaction data comprising a transaction account and a transaction record; the method further comprises the step of determining an abnormal state corresponding to the two-dimensional code and an abnormal threshold value corresponding to the abnormal state based on a comparison result of a transaction feature of a transaction platform and / or a transaction record corresponding to the transaction account and a preset transaction feature, and the abnormal threshold value is used for representing an abnormal degree corresponding to the abnormal two-dimensional code. The method further comprises the step of determining a corresponding target management and control strategy from a plurality of preset management and control strategies based on the abnormal threshold value. In addition, the method also comprises the step of managing and controlling the corresponding abnormal two-dimensional code based on the target management and control strategy.

Description

Technical Field

[0001] The present specification relates to the field of online payment, and more particularly, to a method, apparatus, processor, and computing device for processing transaction data. Background Art

[0002] With the development of Internet technology and science, online virtual resource transactions through the Internet are becoming more and more common. When users conduct transactions on payment platforms or trading platforms, they can submit payment requests by scanning codes, scanning faces, etc., and then confirm the payment amount or enter the amount to be paid, and complete the payment or transaction after security verification. As a result, many criminals also use online payment methods to conduct transactions. Therefore, certain control measures need to be taken to ensure the normal transactions of other users. On this basis, how to conduct fine-grained control over the accounts of people with abnormal transactions is crucial. Summary of the invention

[0003] The embodiments of this specification provide a method, an apparatus, a processor, and a computing device for processing transaction data.

[0004] In the first aspect of the present specification, a method for processing transaction data is provided. The method includes obtaining transaction data in response to a transaction object conducting a transaction by scanning a QR code, and the transaction data includes a transaction account and a transaction record. The method also includes determining an abnormal state corresponding to the QR code and an abnormal threshold corresponding to the abnormal state based on a comparison result of the transaction characteristics of the transaction platform and / or transaction record corresponding to the transaction account and the preset transaction characteristics, and the abnormal threshold is used to characterize the abnormal degree corresponding to the abnormal QR code. The method also includes determining a corresponding target control strategy from a plurality of preset control strategies based on the abnormal threshold. In addition, the method also includes controlling the corresponding abnormal QR code based on the target control strategy.

[0005] In a second aspect of the present specification, a device for processing transaction data is provided. The device includes a transaction record acquisition unit, which is configured to acquire transaction data in response to a transaction object conducting a transaction by scanning a QR code, and the transaction data includes a transaction account and a transaction record. The device also includes an abnormal threshold determination unit, which is configured to determine the abnormal state corresponding to the QR code and the abnormal threshold corresponding to the abnormal state based on the comparison result of the transaction characteristics of the transaction platform and / or transaction record corresponding to the transaction account and the preset transaction characteristics, and the abnormal threshold is used to characterize the abnormal degree corresponding to the abnormal QR code. The device also includes a target control strategy determination unit, which is configured to determine the corresponding target control strategy from multiple preset control strategies based on the abnormal threshold. In addition, the device also includes an abnormal QR code control unit, which is configured to control the corresponding abnormal QR code based on the target control strategy.

[0006] In a third aspect of the present specification, an electronic device is provided. The electronic device includes one or more processors; and a storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors implement the method provided according to the first aspect of the present specification.

[0007] In a fourth aspect of the present specification, a processor is provided, which is configured to execute the method according to the first aspect of the present specification.

[0008] In a fifth aspect of the present specification, a computing device is provided. The computing device includes a memory. The computing device also includes a processor according to the third aspect of the present specification.

[0009] It should be understood that the contents described in the Summary of the Invention are not intended to limit the key or important features of the embodiments of this specification, nor are they intended to limit the scope of this specification. Other features of this specification will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The above and other features, advantages and aspects of the embodiments of the present specification will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein:

[0011] Figure 1 A schematic diagram illustrating an example environment 100 in which various embodiments of the present specification may be implemented;

[0012] Figure 2 A flow chart showing a method 200 for processing transaction data according to some embodiments of the present specification;

[0013] Figure 3 A schematic diagram showing the personnel composition of a target team according to some embodiments of this specification;

[0014] Figure 4 A schematic diagram showing an abnormal threshold for determining an abnormal two-dimensional code according to some embodiments of this specification is shown;

[0015] Figure 5 A schematic diagram for determining abnormal conditions of a two-dimensional code according to some embodiments of this specification is shown; and

[0016] Figure 6 A block diagram of a computing device 600 suitable for implementing an embodiment of the present invention is schematically shown. DETAILED DESCRIPTION

[0017] The embodiments of the present specification will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present specification are shown in the accompanying drawings, it should be understood that the present specification can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present specification. It should be understood that the drawings and embodiments of the present specification are only for exemplary purposes and are not intended to limit the scope of protection of the present specification.

[0018] In the description of the embodiments of this specification, the term "including" and similar terms should be understood as open inclusion, that is, "including but not limited to". The term "based on" should be understood as "based at least in part on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The terms "first", "second", etc. may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0019] As mentioned above, usually, the risk control for abnormal trading groups is to make the transaction fail or directly freeze the related abnormal trading accounts, but such a one-size-fits-all approach may affect other normal transactions of abnormal trading accounts or normal transactions of normal trading accounts. At the same time, there will also be problems such as inaccurate identification, high user disturbance rate, and unclear control effect. Therefore, more fine-grained risk control technology is needed to control abnormal QR codes and abnormal trading accounts.

[0020] To this end, an embodiment of the present specification proposes a scheme for processing transaction data. In an embodiment of the present specification, the method includes obtaining transaction data in response to a transaction object conducting a transaction by scanning a QR code, and the transaction data includes a transaction account and a transaction record. The method also includes determining the abnormal state corresponding to the QR code and the abnormal threshold corresponding to the abnormal state based on the comparison result of the transaction characteristics of the transaction platform and / or transaction record corresponding to the transaction account and the preset transaction characteristics, and the abnormal threshold is used to characterize the degree of abnormality corresponding to the abnormal QR code. The method also includes determining a corresponding target control strategy from a plurality of preset control strategies based on the abnormal threshold. In addition, the method also includes controlling the corresponding abnormal QR code based on the target control strategy.

[0021] In this way, the abnormal threshold corresponding to the abnormal QR code can be determined from multiple dimensions and in all directions, combining the source of the transaction account and the transaction record of the QR code. Based on the abnormal threshold, different control strategies can be determined according to the specific situation, so that fine-grained control can be achieved, and the efficiency and accuracy of QR code management can be improved. In other words, by determining different QR code control strategies based on the abnormal threshold, the QR code can be controlled more flexibly and more finely, so as to ensure the security of transactions while minimizing interference with normal transactions.

[0022] Figure 1 1 is a schematic diagram of an example environment 100 in which various embodiments of the present specification may be implemented. Figure 1 As shown, in the example environment 100, a terminal device 102, a terminal device 104, and a computing device 106 that communicates with the terminal device 102 and the terminal device 104 through a network. The network may include a combination of communication networks such as a public switched telephone network, a local area network, and a wide area network. Among them, the terminal device 102 and the terminal device 104 may be electronic devices with online transaction functions, including but not limited to mobile smart phones, computers (including laptops and desktop computers), tablet electronic devices, personal digital assistants, or smart wearable devices. Among them, a transaction platform may be deployed in the electronic device, and the transaction platform may include a payment platform, an e-commerce platform, a game platform, etc. The computing device 106 may be a server, or any type of stationary or mobile terminal device. It can be understood that each terminal device can communicate with the computing device through a communication network, and each terminal device can communicate with each other through a server.

[0023] In the example environment 100, a first user can register an account on the transaction platform provided by the terminal device 102. After the registration is completed, the terminal device can provide the first user with a first transaction account for online transactions and provide the first user with a corresponding first QR code. The QR code can be a medium for online transactions and can be used for receiving or paying. Similarly, a second user can also register an account on the transaction platform provided by the terminal device 104. The terminal device 104 can provide the second user with a second transaction account and a second QR code.

[0024] The second user (transaction object) can scan the first QR code of the first user through the terminal device 104 to complete the online transaction. In the process of conducting transactions using the first QR code as a medium, the computing device 106 can record the generated transaction records. The transaction record may include the transaction amount, transaction time, transaction location, transaction type, transaction account, etc., and may also include other account information participating in the transaction, such as the investor or recipient of the transaction. It can be understood that the transaction record is the transaction record corresponding to the first QR code of the first transaction account.

[0025] On this basis, after predetermining that the QR code is abnormal, the computing device can determine the abnormal threshold of the abnormal QR code based on the transaction record, the transaction platform of the first transaction account of the first user, or the payment platform of the second transaction account. Among them, the abnormal threshold refers to the abnormal upper limit reached by the abnormal QR code. Or the abnormal threshold can be a quantitative indicator used to characterize the severity of the abnormal QR code. For example, the abnormal threshold of the abnormal QR code can be determined according to the amount of the transaction and the time of the transaction. After determining the abnormal threshold of the abnormal QR code, the corresponding target control strategy can be selected from a plurality of pre-set candidate control strategies according to the abnormal threshold. Among them, different control strategies are control methods for QR codes with different abnormal thresholds. After determining the target control strategy, the abnormal QR code is controlled. For example, the abnormal QR code is invalidated, or the abnormal QR code is monitored regularly.

[0026] In this way, the abnormal threshold corresponding to the abnormal QR code can be determined from multiple dimensions and in all directions, combining the source of the transaction account and the transaction record of the QR code. Based on the abnormal threshold, different control strategies can be determined according to the specific situation, so that fine-grained control can be achieved, and the efficiency and accuracy of QR code management can be improved. In other words, by determining different QR code control strategies based on the abnormal threshold, the QR code can be controlled more flexibly and more finely, so as to ensure the security of transactions while minimizing interference with normal transactions.

[0027] Figure 2 FIG. 2 shows a flow chart of a method 200 for managing a QR code according to some embodiments of the present specification. The method 200 may be Figure 1 The device or electronic device shown in FIG. Figure 2 As shown, in box 202, method 200 may include obtaining transaction data in response to the transaction object conducting a transaction by scanning a QR code, and the transaction data includes a transaction account and a transaction record. The transaction object, such as user A, can conduct a transaction by scanning a QR code. In the process of the transaction, the transaction account corresponding to the QR code can be obtained. That is, the transaction account to which the QR code belongs. The transaction account is the identity representation of the user to whom the QR code belongs on the transaction platform (such as a payment platform) or other websites, for example, an account manually registered by the user in the transaction platform, or a temporary account registered by the transaction platform for the user. There may be transactions between transaction accounts, such as transactions generated based on QR codes. Transactions may include transactions related to electronic resources (such as financial resources and information resources, etc.). Among them, information resources may be game resources, multimedia resources, electronic vouchers, etc. For example, electronic resources may include but are not limited to currency, game equipment, gift vouchers, memberships, points, and point coins, etc.

[0028] In some embodiments, electronic resources or financial resources can be transferred between transaction accounts using a QR code as a medium. For example, a first transaction account can make a payment by scanning a QR code of a second transaction account. The QR code can be a payment code or a receipt code, and the payment code and the receipt code can be a graphical code (such as a barcode and a QR code, etc.) or a sound wave code. It is understood that the QR code can include the identification of the transaction account and the identification of the payment page or the receipt page.

[0029] In some embodiments, the transaction record may include the transaction amount, transaction time, transaction location, transaction type, and transaction account number, etc., and may also include the account information of other parties involved in the transaction, such as the investor or payee. The transaction record may also include the transaction resources, transaction amount, transaction frequency, etc. In some embodiments, the transaction records within the preset time period can be collected from the trading platform, or the transaction records within the preset time period can be obtained from a third party. Among them, the preset time period can be a time period set by the user according to the transaction needs and management and control needs, for example, it can be set to one day, one month, or a time period of 8:00 am to 6:00 pm.

[0030] In one example, after user "Zhang San" completes payment by scanning the QR code payment code through the terminal device, a corresponding transaction record will be generated. In addition to the payee and payee information, transaction amount, transaction time and other data of this transaction, the transaction record also carries the location information of the mobile terminal corresponding to this transaction or the Internet Protocol address of the transaction account.

[0031] In box 204, method 200 may include determining the abnormal state corresponding to the QR code and the abnormal threshold corresponding to the abnormal state based on the comparison result of the transaction characteristics of the transaction platform and / or transaction record corresponding to the transaction account and the preset transaction characteristics, and the abnormal threshold is used to characterize the abnormal degree corresponding to the abnormal QR code. In some embodiments, the transaction characteristics of the transaction record may include but are not limited to the transaction amount, the number of transactions, the transaction time, the transaction location, and the transaction upper limit. Among them, the abnormal threshold can be pre-set by the user according to the management and control requirements, for example, it can be divided into a first abnormal threshold and a second abnormal threshold. It can be understood that which abnormal threshold the abnormal QR code will specifically hit can be determined according to the transaction characteristics of the transaction record of the QR code, or according to the source of the transaction account to which the abnormal QR code belongs. Among them, the source of the transaction account can be which platform the transaction account comes from, for example, from a payment platform, a forum, a network platform, a shopping platform, etc. In other words, it can be determined which platform generates the QR code for the transaction account. Among them, the website can be a normal website, an illegal website, or a mixed website. In some embodiments, the transaction account can be obtained by accessing various networks or platforms, and the source of the transaction account can be determined accordingly.

[0032] It can be understood that if the account of the transaction comes from an illegal channel such as an illegal website (pornographic website, gambling website, etc.), it can be determined that the account of the transaction is abnormal, and all the QR codes corresponding to the transaction account are abnormal. If the account of the transaction comes from a normal channel such as a normal payment platform or a normal entertainment website, the account of the transaction may use part of the QR code for normal transactions and may also use part of the QR code for illegal transactions. On this basis, the abnormal threshold of the abnormal QR code can be further determined by analyzing the transaction record. In other embodiments, the abnormal threshold of the abnormal QR code can also be determined in combination with the credibility of the website. For example, the payment platform itself is a shopping platform, but the account of the transaction has no recent shopping behavior and only has transaction records of fund collection and withdrawal, then the transaction account may have some risky behaviors, and the abnormal threshold of the abnormal QR code corresponding to its abnormal transaction account will be high.

[0033] It is understandable that different abnormal states may correspond to different abnormal thresholds to reflect the different severity. On this basis, after determining the abnormal state of the QR code, its corresponding abnormal threshold can be determined. The abnormal threshold can be set by the user according to actual transaction needs or management and control needs.

[0034] In box 206, method 200 may include determining a corresponding target control strategy from a plurality of preset control strategies based on an abnormal threshold. Among them, different abnormal QR codes have different punishment methods or punishment degrees. What control strategy is used to control the abnormal QR code can be determined according to the abnormal threshold of the abnormal QR code. In some embodiments, the mapping relationship between the abnormal threshold and the control strategy can be set in advance. The mapping relationship can be a mapping relationship table, a mapping relationship model, or a mapping relationship function, etc. According to the mapping relationship, the target control strategy corresponding to the abnormal threshold of the abnormal QR code can be determined. For example, the target control strategy can be to invalidate the abnormal QR code or to blacklist the abnormal QR code. Or it can be to list the abnormal QR code as a monitoring list and monitor the abnormal QR code in real time so as to find problems in time and take corresponding control measures.

[0035] In box 208, method 200 may include controlling abnormal QR codes based on target control strategies. Control refers to monitoring abnormal QR codes according to control strategies and taking corresponding measures to prevent illegal transactions. Or control can also be to control the account of the transaction or the account of the transaction object. For example, control can set the transaction account to the abnormal account list, or it can invalidate the abnormal QR code (i.e., prohibit the abnormal QR code from being used in future transactions), or it can impose a certain fine on the transaction account to which the abnormal QR code belongs or the platform where the abnormal QR code is located.

[0036] In this way, the abnormal threshold corresponding to the abnormal QR code can be determined from multiple dimensions and in all directions, combining the source of the transaction account and the transaction record of the QR code. Based on the abnormal threshold, different control strategies can be determined according to the specific situation, so that fine-grained control can be achieved, and the efficiency and accuracy of QR code management can be improved. In other words, by determining different control strategies for abnormal QR codes based on the abnormal threshold, abnormal QR codes can be controlled more flexibly and more finely, so that while ensuring transaction security, interference with normal transactions can be minimized as much as possible.

[0037] In some embodiments, users can collect links or related information of illegal gambling, pornography and other websites through complaints, reports, intelligence discovery and other channels, and obtain transaction accounts by simulating the behavior of real users. For example, manual operations can be simulated to automatically open the platform of illegal websites, and registration, login, recharge and other operations can be performed according to the preset process to obtain the transaction account and the QR code corresponding to the transaction account.

[0038] In actual situations, people who engage in abnormal transactions usually have their own teams, and the teams have their own unique structures and personnel. After determining the transaction account (abnormal transaction account) corresponding to a certain abnormal QR code, the abnormal transaction account can be expanded. Generally, users who conduct illegal transactions usually have a certain correlation. For example, a team usually collects money for others in one place and earns a certain percentage of commission, or multiple accounts repeatedly remit money to the same account in a similar time period. On this basis, the degree of abnormality of the candidate transaction account can be determined according to the degree of correlation between the candidate transaction account and the abnormal transaction account. Among them, the candidate transaction account can be an account from the same website or platform as the abnormal transaction account, or it can be a transaction account that has a certain relationship with the abnormal transaction account (for example, in the same geographical location or similar transaction time). The degree of correlation can be used to characterize the degree of correlation or similarity between the transaction account and the abnormal transaction account. From another perspective, the degree of similarity with the abnormal transaction account can reflect the possibility of whether the candidate transaction account is abnormal to a certain extent.

[0039] In reality, if there is no clear social relationship (such as friends, colleagues, etc.) between the two users corresponding to the two trading accounts, but there is a large amount of capital transactions, this may be an abnormal signal. Because under normal circumstances, users are more likely to conduct large-scale capital transactions with people with whom they have social relationships. On this basis, the degree of association between the trading account and the abnormal trading account can be determined based on the social relationship and capital relationship between the trading account and the abnormal trading account. Among them, social relationships refer to the interactive relationships between people, including many types, such as but not limited to family relationships, friend relationships, cooperative relationships, husband-wife relationships, etc. Of course, social relationships can also be simply divided into mutual acquaintance relationships and non-acquaintance relationships. Among them, the capital relationship can include capital flow records, that is, which trading account the funds flow from and into which trading account. The capital flow record can include the amount of the flow, the number of flows, and the objects of the flow, etc.

[0040] It can be understood that the social relationship between two people can reflect the financial transactions between the two people to a certain extent. If the two people are not so familiar (that is, the closeness of the social relationship is not high), such as only colleagues or ordinary friends, the financial transactions between the two people may not be so close, and the amount will not be large. If the closeness of the social relationship between the two people is high (for example, higher than the closeness threshold), the financial transactions between the two people may be relatively close, and the amount may also be large. Then, the degree of association between the candidate transaction account and the abnormal transaction account can be determined based on the social relationship and the financial relationship. It can be understood that the degree of association is negatively correlated with the closeness of the social relationship and positively correlated with the financial relationship (such as the transfer amount and the number of transfers contained in the financial relationship). In this way, it is possible to spread to the transaction accounts related to it based on the consideration of multiple factors with the abnormal transaction account as the center, so that more abnormal transaction accounts can be directly and accurately determined.

[0041] In some embodiments, the location information of the payer or payee can be recorded during the transaction process. Among them, the location information may include any one or more of a geographic area identifier, longitude and latitude, a geographic location code, and a network address (Internet Protocol Address, IP). Among them, the geographic area identifier can be used to identify a geographic area (for example, it can be used to identify a country, a city, a region, etc.). In addition, the geographic area represented by the network address can be the geographic area mapped by the network address. Since the personnel in the team corresponding to the abnormal transaction group often operate in the same place, the abnormal degree of the candidate transaction account can be determined according to the correlation or similarity between the location of the candidate transaction account and the abnormal transaction account. In addition, the abnormal transaction group in the same team usually uses the mobile phone or device distributed by the team to conduct illegal transactions. On this basis, the abnormal degree of the candidate transaction account can also be determined by combining the medium corresponding to the candidate transaction account and the medium of the abnormal transaction account. Among them, the medium refers to the equipment and network form used by the transaction account login platform such as the transaction platform (for example, through a wireless network connection or a wired connection, etc.).

[0042] It is understood that the degree of association can be expressed in the form of an association score or by a grade. In some embodiments, the association relationship can be determined based on the geographical location of the transaction account and the medium corresponding to the transaction account. For example, the first association score can be determined based on the similarity of the location information (such as IP address, geographical location, etc.) of the candidate transaction account and the abnormal transaction account. Among them, the higher the similarity between the two transaction accounts, the closer the two accounts are geographically, and the higher the possibility of abnormality in the candidate transaction account. For example, a similarity algorithm can be used to determine the similarity between the geographical location of the candidate transaction account and the geographical location of the abnormal transaction account. Among them, the similarity algorithm may include but is not limited to cosine similarity, Pearson correlation coefficient, Euclidean distance, etc. It is understood that the similarity between the geographical location of the candidate transaction account and the geographical location of the abnormal transaction account is proportional to the first association score, and the higher the similarity between the two, the higher the first association score.

[0043] Similarly, based on the similarity between the communication medium of the candidate transaction account and the communication medium of the abnormal transaction account, a second association score can be determined. The second association score is also proportional to the similarity between the two, which will not be introduced in this specification. When determining an association score and a second association score, the weighted sum of the first association score and the second association score can be determined according to the weight values ​​corresponding to the two, and the weighted sum can be used as the association score between the candidate transaction account and the abnormal transaction account. Among them, the weight value of the first association score can be used to characterize the importance of the geographic location dimension in judging the degree of association. The weight value can be set by the user according to actual needs, for example, it can be set to 0.6, 0.7, etc. Similarly, the second association score can be used to characterize the importance of the medium dimension in judging the degree of association.

[0044] In this way, multiple dimensions can be combined to determine the degree of correlation between candidate transaction accounts and abnormal transaction accounts, so as to determine a more accurate degree of correlation and provide strong data support for subsequent management and control decisions of candidate transaction accounts.

[0045] In addition, the degree of association can also be determined by combining multiple factors such as social relationship, financial relationship, geographical location and medium. For example, the association score can be determined based on the weighted sum of social relationship, financial relationship, geographical location and medium. In one example, the association score can be determined using the following formula: association score = similarity of social relationship◇weight 1+similarity of financial relationship◇weight 2+similarity of geographical location◇weight 3+similarity of medium◇weight 4. In this way, the degree of association between the candidate transaction account and the abnormal transaction account can be determined more comprehensively.

[0046] Figure 3 FIG. 1 is a schematic diagram showing the personnel composition of a team according to some embodiments of this specification. Figure 3 As shown, in the case where it is determined that the transaction account corresponding to member A is an abnormal transaction account, it can be determined whether the transaction accounts of other members are abnormal based on the association relationship between the transaction accounts of other members and the transaction account of member A, with member A as the center. After determining the relevant abnormal transaction accounts, the personnel composition and structure of the target team can be constructed based on this. For example, it can be determined whether member B is an abnormal transaction account based on the degree of association between member A and member B. For example, in the above manner, based on the degree of association between the transaction accounts of member A and member B, it can be determined that the transaction account corresponding to member B is an abnormal transaction account. In the case where it is determined that the transaction account of member B is an abnormal transaction account, it can be determined that the transaction account of member C is also an abnormal transaction account based on the degree of association between the transaction account of member C and the transaction account of member B.

[0047] In addition, since both member A and member B have a certain degree of association with member C, in order to more accurately determine the abnormality of member C's trading account, it is possible to determine whether the trading account corresponding to member C is an abnormal trading account based on the degree of association between member A's trading account, member B's trading account and member C's trading account. For example, the degree of abnormality of member C's trading account can be determined according to the following formula: Abnormality = degree of association (A, C)◇weight 1+degree of association (B, C)◇weight 2. Wherein, the degree of association (A, C) can be the degree of association between member A's trading account and member C's trading account, and the degree of association (B, C) can be the degree of association between member B's trading account and member C's trading account. Wherein, weight 1 is the weight value corresponding to the degree of association (A, C), which is used to characterize the degree of influence of the degree of association (A, C) on the degree of abnormality. Similarly, weight 2 is the weight value corresponding to the degree of association (B, C), which is used to characterize the degree of influence of the degree of association (B, C) on the degree of abnormality. Weight 1 and weight 2 can be set by the user according to specific circumstances, for example, weight 1 can be set to 0.5, and weight 2 can be set to 0.5. It can be understood that the values ​​of weight 1 and weight 2 can be the same or different.

[0048] Based on the above-mentioned similar abnormal situation determination method, it can also be determined that the transaction accounts corresponding to member C, member D, and member E are all abnormal transaction accounts, and the corresponding QR codes are all abnormal QR codes. By integrating the results of the association analysis, a complete abnormal account network diagram can be formed, which will facilitate subsequent risk analysis and control. In other words, in this way, based on the connection relationship between each member, the network structure and participants of abnormal trading activities can be fully revealed, thereby minimizing the risk of illegal trading behavior and protecting the security of the trading system and the legitimate rights and interests of users.

[0049] Since the transaction account uses the QR code as the medium for transactions, a variety of transaction information will be recorded to form the transaction record corresponding to the QR code. In this case, the transaction characteristics of the transaction record can reflect to a certain extent whether the QR code is used for illegal transactions. Among them, the transaction characteristics of the transaction record may include the transaction amount, transaction time (used to indicate the time when the transaction occurred), transaction location (used to indicate the location where the transaction occurred, which can be the geographical location of the payee or the geographical location of the payee), the two parties to the transaction (such as the resource beneficiary of the transaction), the number of transactions, etc. Among them, the transaction amount may include the amount of a single transaction, the amount of multiple transactions, the transaction amount, and the maximum transaction amount. The transaction amount refers to the value of a specific amount of currency or other quantified items in a transaction.

[0050] It can be understood that the abnormal state and abnormal threshold of the QR code can be determined based on an information in the transaction record. For example, the abnormal state of the QR code can be determined based on the transaction amount information in the transaction record. For example, when the transaction amount corresponding to the QR code is greater than the preset transaction amount threshold, the QR code can be determined to be abnormal. Among them, the abnormality can be used to indicate that the QR code is used for illegal transactions, and can also be used to indicate that the QR code may have transaction risks. What information is specifically used to characterize can be further determined based on the abnormal threshold. The higher the abnormal threshold, the higher the degree of transaction risk. Among them, the abnormal threshold can be determined based on the difference between the transaction amount and the preset transaction amount threshold. Or when the number of transactions of the QR code within a preset time period is greater than the preset number threshold, the QR code can also be determined to be abnormal. The abnormal threshold corresponding to the abnormal QR code can be determined based on the difference between the number of transactions and the preset number of transactions threshold. The larger the difference, the larger the abnormal threshold hit. Among them, the preset number threshold and the preset amount threshold can be set by the user, for example, the preset number threshold can be set to 30 times, 20 times, etc., and the preset amount threshold can be set to 100,000, 200,000, etc. Of course, the abnormality of the QR code can also be determined based on the transaction location or other information.

[0051] In some embodiments, the abnormal state and abnormal threshold of the QR code can also be determined in combination with the two pieces of information. For example, the abnormal situation of the QR code can be determined based on the transaction amount in the transaction record and the transaction parties. For example, when the transaction amount exceeds the amount of a single transaction and there is no social relationship between the transaction parties or the closeness of the social relationship is less than the set threshold, the QR code can be determined to be abnormal. Or when the QR code has multiple large transactions in a short period of time and there is no social relationship or a partial social relationship between the user who generated the large transaction and the user corresponding to the transaction account, the QR code can also be determined to be abnormal. Of course, in order to make the judgment based on the above factors more accurate, the specific background of the transaction, the background information of the transaction parties, and the legality and compliance of the transaction can be further investigated. Based on this information, the abnormal situation of the QR code (such as whether it is abnormal and the degree of abnormality) is comprehensively considered.

[0052] Alternatively, the abnormal state and abnormal threshold of the QR code can also be determined based on the transaction amount and the number of transactions. For example, the first abnormal score can be determined based on the transaction amount, and the second abnormal score can be determined based on the number of transactions. Based on the first abnormal score and the second abnormal score, the abnormal threshold corresponding to the QR code can be determined. The first abnormal score can be determined based on the difference between the transaction amount and the preset transaction amount, and the second abnormal score can be determined based on the difference between the number of transactions and the preset number of transactions. Based on the statistical value of the first abnormal score and the second abnormal score, the abnormal score corresponding to the QR code is determined. The abnormal score can be used to reflect the abnormal degree of the QR code. According to the abnormal score, the abnormal threshold corresponding to the abnormal QR code can be determined. Among them, the statistical value can be a sum value, a weighted sum value, an average value, etc. Taking the weighted sum value as an example, the abnormal score corresponding to the QR code can be determined using the following formula: abnormal score = first abnormal score◇first weight+second abnormal score◇second weight.

[0053] Of course, in some embodiments, all the information included in the transaction record may be comprehensively considered to determine the abnormality of the QR code. Figure 4 FIG. 1 is a schematic diagram showing an abnormal threshold value for determining an abnormal two-dimensional code according to some embodiments of the present specification. Figure 4 As shown, the abnormal threshold corresponding to the abnormal QR code can be determined according to the transaction amount, transaction number, transaction time, transaction parties, transaction location, etc. contained in the transaction record. For example, the first abnormal score, the second abnormal score, the third abnormal score, the fourth abnormal score, and the fifth abnormal score can be determined according to the transaction number, transaction amount, transaction parties, transaction location, and transaction time. Based on the statistical values ​​of the first abnormal score, the second abnormal score, the third abnormal score, the fourth abnormal score, and the fifth abnormal score, such as the weighted sum value, the abnormal threshold corresponding to the QR code can be determined. It can be understood that the abnormal threshold is proportional to the weighted sum value.

[0054] In this way, the transaction records can be displayed in the form of a chart, so that the changes in the transaction records can be intuitively understood. In addition, by comprehensively considering all the information in the transaction records, the abnormal situation of the QR code can be obtained more intuitively and accurately.

[0055] It can be understood that historical transaction records reflect the past transaction behavior patterns of transaction accounts. By analyzing historical transaction records, we can understand the regular transaction characteristics of transaction accounts, such as transaction frequency, transaction amount, transaction time, etc. On this basis, historical transaction records can also be used as indicators to evaluate the abnormality of QR codes to a certain extent. Among them, historical transaction records can be obtained from databases, log files, or from third-party websites. For example, the abnormality of QR codes can be determined based on the comparison results of historical transaction records and transaction records. When certain information in the transaction record is significantly different from the normal transaction pattern in the historical transaction record, such as abnormal transaction amount, transaction time that does not conform to the norm, etc., it can be determined that the transaction record is abnormal, that is, the QR code is abnormal. On this basis, according to the difference between the historical transaction record and the transaction record, the abnormal threshold corresponding to the abnormal QR code can be determined.

[0056] In some embodiments, if a QR code has been complained about before, the abnormal threshold of the QR code can be determined based on the complaint. The complaint situation may include the historical time of the complaint, the number of complaints, and the content of the complaint. On this basis, if the QR code has been complained about before and the number of complaints is large, it can be indicated that the probability of the QR code being in an abnormal situation is high, that is, the abnormal threshold of the QR code is high.

[0057] In some embodiments, a user on a normal payment platform may have multiple QR codes, some of which can be used for normal consumption or transactions, while some QR codes may be used for illegal transactions. In addition, multiple transaction accounts on illegal websites may be used for illegal transactions, that is, one or more QR codes corresponding to a transaction account are abnormal. On this basis, the abnormality of the QR code can be comprehensively judged in combination with the source of the transaction account and the transaction record of the QR code.

[0058] Figure 5 FIG. 2 shows a schematic diagram for determining abnormal conditions of a two-dimensional code according to some embodiments of the present specification. Figure 5 As shown, the source of the transaction account can be determined based on the information or other information carried by the transaction account. The source refers to which payment platform or website the transaction account is registered on. After determining the source of the transaction account, it can be determined whether the transaction account is from a normal website. For example, it can be determined whether the transaction account is from a normal payment website such as Alipay and an e-commerce website such as Taobao.

[0059] like Figure 5As shown, when it is determined that the transaction account originates from an illegal website, it can be directly determined that all QR codes corresponding to the transaction account are abnormal QR codes. Among them, illegal websites can be gambling, pornography and other websites. When it is determined that the transaction account originates from a normal website or a mixed website, it is necessary to further combine the information of the QR code of the transaction account to determine the abnormality of the QR code. Among them, the information of the QR code can be determined based on the transaction record corresponding to the QR code. For example, the abnormal threshold of the QR code can be determined according to the transaction record in the manner provided in the above embodiment.

[0060] In some embodiments, the abnormal threshold of the QR code can be used to determine the control measures of the QR code. For example, taking the abnormal threshold as an example, the range of the abnormal threshold can be divided into multiple intervals. For example, 0-20 points can be used as the first interval, 20-50 points can be used as the second interval, and 50-100 points can be used as the third interval. Different intervals correspond to different control measures. For example, the abnormal threshold of the abnormal QR code in the first interval is low, indicating that the possibility of illegal transactions in the QR code is not high, but there is still a certain abnormal probability. On this basis, the control measures corresponding to the first interval can be to include the QR code in the monitoring list for regular testing. For example, a transaction early warning mechanism can be set for the detection list, so that relevant personnel can be notified in time when an abnormal transaction mode appears in the QR code.

[0061] The abnormal threshold of the QR code in the second interval is at a medium level, indicating that the abnormal QR code may contain illegal transactions, but the possibility is not high. On this basis, the control measures corresponding to the second interval can add transaction restrictions to abnormal QR codes. For example, the transaction amount or the number of transactions can be limited. In order to further determine the security of the transaction, additional identity verification can be provided when using the abnormal QR code for transactions, such as mobile phone verification code verification or face verification.

[0062] The abnormal threshold of abnormal QR codes in the third interval is high, indicating that there are illegal transactions in the abnormal QR codes in this interval. Then the corresponding control measure for this interval is to invalidate the QR code, that is, the QR code can no longer be used as a transaction medium. Of course, the spread of illegal transactions can also be limited by imposing a certain fine. In this way, based on the form of controlling abnormal QR codes in different intervals, potential risks can be managed more accurately to ensure the security and compliance of transactions.

[0063] Figure 6 The block diagram of a computing device 600 suitable for implementing an embodiment of the present invention is schematically shown. The computing device 600 may be a computer system for implementing the execution Figure 2 The apparatus of the method 200 is shown. Figure 6As shown, the computing device 600 includes a processing unit (CPU) 601, which can perform various appropriate actions and processes according to computer program instructions stored in a read-only memory (ROM) 602 or computer program instructions loaded from a storage unit 608 into a random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the computing device 600 can also be stored. The CPU 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0064] Multiple components in the computing device 600 are connected to the I / O interface 605, including: an input unit 606, an output unit 607, and a storage unit 608. The processing unit 601 performs the various methods and processes described above, such as executing the method 200. For example, in some embodiments, the various processes or operations described above can be implemented as a computer software program, which is stored in a machine-readable medium, such as the storage unit 608. In some embodiments, part or all of the computer program can be loaded and / or installed on the computing device 600 via the ROM 602 and / or the communication unit 609. When the computer program is loaded into the RAM 603 and executed by the CPU 601, the various methods and processes described above can be executed, such as executing one or more operations of the method 200. Alternatively, in other embodiments, the CPU 601 can be configured to execute the various methods and processes described above, such as executing one or more actions of the method 200, by any other appropriate means (for example, by means of firmware).

[0065] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0066] The computer program instructions for performing the operation of the present invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed entirely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be personalized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present invention.

[0067] These computer-readable program instructions can be provided to a processor in a voice interaction device, a general-purpose computer, a special-purpose computer, or a processing unit of other programmable data processing devices, thereby producing a machine, so that when these instructions are executed by the processing unit of a computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other device to work in a specific manner.

[0068] The above is a description of a specific embodiment of the present specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0069] The embodiments of the present invention have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

[0070] The above are only optional embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for processing transaction data, comprising: In response to the transaction object conducting a transaction by scanning the QR code, acquiring transaction data, wherein the transaction data includes the transaction account number and transaction record; Based on the comparison result of the transaction platform corresponding to the transaction account and / or the transaction characteristics of the transaction record with the preset transaction characteristics, determine the abnormal state corresponding to the QR code and the abnormal threshold corresponding to the abnormal state, and the abnormal threshold is used to characterize the abnormal degree corresponding to the abnormal QR code; Based on the abnormal threshold, determining a corresponding target control strategy from a plurality of preset control strategies; as well as Based on the target control strategy, the corresponding abnormal QR code is controlled.

2. The method according to claim 1, further comprising: Based on the abnormal threshold of the QR code, determine the corresponding abnormal transaction account; Acquire candidate transaction accounts related to the abnormal transaction account; Determining the degree of association between the candidate transaction account and the abnormal transaction account; as well as Based on the degree of association, the degree of abnormality of the candidate transaction account is determined.

3. The method according to claim 2, wherein determining the degree of association between the candidate transaction account and the abnormal transaction account comprises: Acquiring the social relationship and financial relationship between the candidate transaction account and the abnormal transaction account; as well as Based on the type and closeness of the social relationship and the financial relationship, the degree of association between the candidate transaction account and the abnormal transaction account is determined.

4. The method according to claim 2, wherein determining the degree of association between the candidate transaction account and the abnormal transaction account comprises: Acquire the first location information and the first communication medium of the candidate transaction account and the second location information and the second communication medium of the abnormal transaction account; Determining a first degree of association based on a degree of similarity between the first location information and the second location information; determining a second degree of association based on a degree of similarity between the first communication medium and the second communication medium; as well as The degree of association between the candidate transaction account and the abnormal transaction account is determined based on the first degree of association, a first weight value corresponding to the first degree of association, the second degree of association, and a second weight value corresponding to the second degree of association.

5. The method according to claim 1, wherein the transaction characteristics of the transaction record include the number of transactions and the transaction amount, and based on the transaction platform corresponding to the transaction account and / or the comparison result of the transaction characteristics of the transaction record with the preset transaction characteristics, determining the abnormal state corresponding to the QR code and the abnormal threshold corresponding to the abnormal state includes: Determining a first anomaly score based on a comparison result of the transaction amount and the preset transaction amount threshold; Determining a second anomaly score based on a comparison result of the number of transactions with a preset transaction number threshold; as well as Determining an anomaly score corresponding to the QR code of the transaction account based on the first anomaly score and the second anomaly score; Based on the anomaly score, an anomaly threshold corresponding to the QR code is determined.

6. The method according to claim 1, wherein based on the comparison result between the transaction platform corresponding to the transaction account and / or the transaction characteristics of the transaction record and the preset transaction characteristics, determining the abnormal state corresponding to the QR code and the abnormal threshold corresponding to the abnormal state comprises: Determine the platform anomaly score of the account number for the transaction based on the transaction platform corresponding to the account number for the transaction; Determining a transaction anomaly score based on a comparison result of the transaction feature of the transaction record with a preset transaction feature; and Based on the platform anomaly score and the transaction anomaly score, an anomaly threshold corresponding to the QR code is determined.

7. The method according to claim 6, wherein determining the platform anomaly score of the transaction account based on the transaction platform corresponding to the transaction account comprises: Determine whether the account of the transaction comes from a normal trading platform; as well as In response to the transaction account originating from an abnormal transaction platform, determining that the transaction account is abnormal; as well as Based on the type of the abnormal transaction website, a platform anomaly score of the transaction account is determined.

8. The method according to claim 1, wherein based on the comparison result of the transaction platform corresponding to the transaction account and / or the transaction characteristics of the transaction record with the preset transaction characteristics, determining the abnormal state corresponding to the QR code and the abnormal threshold corresponding to the abnormal state comprises: Obtaining historical transaction records corresponding to the QR code; as well as Based on the transaction platform corresponding to the transaction account, the transaction characteristics of the transaction record, and the historical transaction record characteristics of the historical transaction record, the abnormal state corresponding to the QR code is determined.

9. The method according to claim 1, wherein based on the comparison result between the transaction platform corresponding to the transaction account and / or the transaction characteristics of the transaction record and the preset transaction characteristics, determining the abnormal state corresponding to the QR code and the abnormal threshold corresponding to the abnormal state comprises: Based on the social relationship between the transaction object and the user corresponding to the transaction account, the abnormal state corresponding to the QR code is determined.

10. The method according to claim 1, wherein based on the abnormal threshold, determining a corresponding target control strategy from a plurality of preset control strategies comprises: When the abnormal threshold is within the first abnormal threshold interval, the target control strategy is determined to invalidate the QR code.

11. The method according to claim 1, wherein based on the abnormality level interval in which the abnormality level is located, determining the control method of the QR code of the transaction account comprises: When the abnormal threshold is within the second abnormal threshold interval, the target control strategy is determined to monitor the transaction record of the QR code within a preset time period and return abnormal reminder information.

12. A device for processing transaction data, comprising: A transaction record acquisition unit, configured to acquire transaction data in response to a transaction object performing a transaction by scanning a QR code, wherein the transaction data includes an account number of the transaction and a transaction record; an abnormality threshold determination unit, configured to determine the abnormal state corresponding to the QR code and the abnormality threshold corresponding to the abnormal state based on a comparison result between the transaction platform corresponding to the transaction account and / or the transaction characteristics of the transaction record and the preset transaction characteristics, wherein the abnormality threshold is used to characterize the abnormality degree corresponding to the abnormal QR code; a target control strategy determination unit, configured to determine a corresponding target control strategy from a plurality of preset control strategies based on the abnormality threshold; as well as The abnormal QR code control unit is configured to control the corresponding abnormal QR code based on the target control strategy.

13. A processor, configured to execute the method according to any one of claims 1 to 11.

14. A computing device comprising: Memory; as well as A processor according to claim 13.

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