Test processing method, device, equipment and system

Abstract

The embodiments of the present specification provide a test processing method, apparatus, device and system, wherein the method includes: determining a target virtual fraud scenario that matches a user to be tested from a plurality of pre-constructed virtual fraud scenarios; performing display processing of the target virtual fraud scenario based on the acquired scenario construction data of the target virtual fraud scenario; acquiring behavior data corresponding to the operating behavior of the user to be tested in the target virtual fraud scenario; and generating a test result for the user to be tested based on the acquired behavior data.

Description

Technical Field

[0001] This document relates to the field of computer technology, and in particular to a test processing method, device, equipment and system. Background Art

[0002] With the continuous development and popularization of the Internet, it is not uncommon for the black industry to use the Internet to defraud users. This not only causes serious losses to users' assets, but also undermines social stability. At present, in order to enhance users' anti-fraud awareness, fraud cases and fraud methods are promoted to users through text or video. However, in this publicity method, users cannot perform actual operations, have a weak sense of immersion, and cannot deeply experience the professional fraudulent techniques of the black industry. Therefore, the effect of enhancing users' anti-fraud awareness is not ideal. Summary of the invention

[0003] One or more embodiments of the present specification provide a test processing method. The method includes determining a target virtual fraud scenario that matches a user to be tested from among a plurality of pre-constructed virtual fraud scenarios. Performing display processing of the target virtual fraud scenario based on the scenario construction data of the target virtual fraud scenario obtained. Obtaining behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario. Generating a test result of the user to be tested based on the behavior data.

[0004] One or more embodiments of the present specification provide a test processing method. The method includes determining a target virtual fraud scenario that matches a user to be tested from a plurality of pre-constructed virtual fraud scenarios. Performing display processing of the target virtual fraud scenario based on the scenario construction data of the target virtual fraud scenario. Obtaining behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario. Calling a smart contract in a blockchain system, and generating a test result of the user to be tested based on the behavior data based on the smart contract. Saving the test result in the blockchain system.

[0005] One or more embodiments of the present specification provide a test processing device. The device includes a determination module, which determines a target virtual fraud scenario that matches a user to be tested from a plurality of pre-constructed virtual fraud scenarios. The device also includes a processing module, which performs display processing of the target virtual fraud scenario based on the acquired scenario construction data of the target virtual fraud scenario. The device also includes an acquisition module, which acquires behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario. The device also includes a generation module, which generates a test result of the user to be tested based on the behavior data.

[0006] One or more embodiments of the present specification provide a test processing device. The device includes a determination module, which determines a target virtual fraud scenario that matches a user to be tested among a plurality of pre-constructed virtual fraud scenarios. The device also includes a processing module, which performs display processing of the target virtual fraud scenario based on the scenario construction data of the target virtual fraud scenario obtained. The device also includes an acquisition module, which acquires behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario. The device also includes a generation module, which calls a smart contract in a blockchain system, and generates a test result of the user to be tested based on the behavior data based on the smart contract. The device also includes a saving module, which saves the test result to the blockchain system.

[0007] One or more embodiments of the present specification provide a test processing system. The system includes a server and a client. The server determines a target virtual fraud scenario that matches a user to be tested from a plurality of pre-constructed virtual fraud scenarios. The acquired scenario construction data of the target virtual fraud scenario is sent to the client of the user to be tested. The behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario is received from the client. The test result of the user to be tested is generated according to the behavior data. The client displays the target virtual fraud scenario according to the received scenario construction data sent by the server. The behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario is acquired. The behavior data is sent to the server.

[0008] One or more embodiments of the present specification provide a test processing system. The system includes a blockchain system and a client. The blockchain node in the blockchain system determines a target virtual fraud scenario that matches the user to be tested among a plurality of pre-constructed virtual fraud scenarios. The acquired scenario construction data of the target virtual fraud scenario is sent to the client of the user to be tested. The behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario sent by the client is received. The smart contract in the blockchain system is called, and the test result of the user to be tested is generated based on the behavior data based on the smart contract. The test result is saved in the blockchain system. The client displays the target virtual fraud scenario according to the received scenario construction data sent by the blockchain node. The behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario is obtained. The behavior data is sent to the blockchain node.

[0009] One or more embodiments of the present specification provide a data processing device. The device includes a processor. The device also includes a memory arranged to store computer executable instructions. When the computer executable instructions are executed, the processor determines a target virtual fraud scenario that matches a user to be tested among a plurality of pre-constructed virtual fraud scenarios. According to the scenario construction data of the target virtual fraud scenario obtained, the display processing of the target virtual fraud scenario is performed. The behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario is obtained. The test result of the user to be tested is generated according to the behavior data.

[0010] One or more embodiments of the present specification provide a data processing device. The device includes a processor. The device also includes a memory arranged to store computer executable instructions. When the computer executable instructions are executed, the processor determines a target virtual fraud scenario that matches a user to be tested among a plurality of pre-constructed virtual fraud scenarios. According to the acquired scenario construction data of the target virtual fraud scenario, the display processing of the target virtual fraud scenario is performed. The behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario is obtained. The smart contract in the blockchain system is called, and the test result of the user to be tested is generated according to the behavior data based on the smart contract. The test result is saved in the blockchain system.

[0011] One or more embodiments of the present specification provide a storage medium. The storage medium is used to store computer executable instructions. When the computer executable instructions are executed by a processor, a target virtual fraud scenario that matches a user to be tested is determined from a plurality of pre-constructed virtual fraud scenarios. Based on the scenario construction data of the target virtual fraud scenario obtained, a display process of the target virtual fraud scenario is performed. Behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario is obtained. A test result of the user to be tested is generated based on the behavior data.

[0012] One or more embodiments of the present specification provide a storage medium. The storage medium is used to store computer executable instructions. When the computer executable instructions are executed by a processor, a target virtual fraud scenario that matches a user to be tested is determined from a plurality of pre-constructed virtual fraud scenarios. Based on the acquired scenario construction data of the target virtual fraud scenario, display processing of the target virtual fraud scenario is performed. Behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario is obtained. A smart contract in a blockchain system is called, and a test result of the user to be tested is generated based on the smart contract and the behavior data. The test result is saved in the blockchain system. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate one or more embodiments of this specification or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0014] Figure 1 A first flow chart of a test processing method provided for one or more embodiments of this specification;

[0015] Figure 2 A second flow chart of a test processing method provided for one or more embodiments of this specification;

[0016] Figure 3 A third flow chart of a test processing method provided for one or more embodiments of this specification;

[0017] Figure 4 A fourth flow chart of a test processing method provided for one or more embodiments of this specification;

[0018] Figure 5 A fifth flow chart of a test processing method provided for one or more embodiments of this specification;

[0019] Figure 6 A sixth flow chart of a test processing method provided for one or more embodiments of this specification;

[0020] Figure 7 A seventh flow chart of a test processing method provided for one or more embodiments of this specification;

[0021] Figure 8 A schematic diagram of a first module composition of a test processing device provided for one or more embodiments of this specification;

[0022] Fig. 9 A schematic diagram of a second module composition of a test processing device provided for one or more embodiments of this specification;

[0023] Fig.10 A first schematic diagram of a test processing system provided for one or more embodiments of this specification;

[0024] Fig.11 A second schematic diagram of a test processing system provided for one or more embodiments of this specification;

[0025] Fig.12A schematic diagram of the structure of a test processing device provided for one or more embodiments of this specification. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below in conjunction with the drawings in one or more embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of them. Based on one or more embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this document.

[0027] Figure 1 The present invention provides a flowchart of a test processing method for one or more embodiments of the present invention. The method can be applied to a server, wherein the server can be an independent server or a server cluster composed of multiple servers. Figure 1 As shown, the method may include the following steps:

[0028] Step S102, determining a target virtual fraud scenario that matches the user to be tested from among a plurality of pre-constructed virtual fraud scenarios;

[0029] In order to enhance the user's anti-fraud awareness and let the user experience the fraudulent means of the fraudster more vividly, in one or more embodiments of this specification, multiple virtual fraud scenarios for user testing are constructed in advance based on the current fraud modes and fraud means. It can be understood that the virtual fraud scenario is a virtual environment that makes the user feel immersed. When the user is in it, he has a stronger sense of substitution and physical sensation, and can experience the corresponding fraud mode and fraud means more realistically. Among them, the fraud mode includes but is not limited to online shopping fraud, gambling fraud, and naked chat fraud; the fraud means include which information is sent to the user, which operations are guided to the user, and which operation interfaces are guided to the user. Each virtual fraud scenario can correspond to a fraud mode and at least one fraud means, as well as at least one transaction. In order to avoid the user to be tested from a priori believing that all transactions are fraudulent, the transactions corresponding to each virtual fraud scenario may include fraudulent transactions based on the corresponding fraud means, and may also include non-fraudulent normal transactions.

[0030] Step S104, performing display processing of the target virtual fraud scenario according to the acquired scenario construction data of the target virtual fraud scenario;

[0031] Specifically, the server sends the acquired scenario construction data of the target virtual fraud scenario to the client corresponding to the user to be tested, and the client displays the target virtual fraud scenario according to the scenario construction data. Among them, the scenario construction data may include interface rendering data, environment construction data, voice data, etc. The client can be an independent application (Application, App for short) installed in the terminal device of the user to be tested, or it can be a small program embedded in other applications. The client can also be a terminal device set in a specific environment for each user to perform anti-fraud testing, such as a virtual reality device set in a shopping mall that can experience a virtual environment.

[0032] Step S106, obtaining behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario;

[0033] Specifically, the behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario sent by the client is received. The operation behavior of the user to be tested includes input behavior, touch behavior, voice behavior, etc.; the behavior data includes input data, touch data, voice data, etc.

[0034] Step S108: Generate a test result of the user to be tested based on the behavior data.

[0035] Specifically, based on the behavioral data of the user to be tested, determine whether the fraud pattern and fraud means corresponding to the target virtual fraud scenario are successful in defrauding the user to be tested. If so, generate a test result indicating that the user to be tested has been successfully defrauded; if not, generate a test result indicating that the user to be tested has failed to be defrauded.

[0036] In one or more embodiments of the present specification, a target virtual fraud scenario that matches the user to be tested is determined among multiple pre-constructed virtual fraud scenarios; based on the acquired scenario construction data of the target virtual fraud scenario, the target virtual fraud scenario is displayed, and the behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario is obtained, and the test results of the user to be tested are generated based on the behavior data. Thus, based on the target virtual fraud scenario that matches the user to be tested, the user to be tested is subjected to anti-fraud test processing, which allows the user to perform actual operations therein, giving the user a stronger sense of immersion and physical sensation, and allowing the user to more truly experience the fraudulent means, the urgency of time, the temptation of benefits, or potential heavy losses, etc. It is beneficial for the user to be tested to establish an effective method for identifying fraud, so that when encountering corresponding fraudulent means in real life, the risk can be quickly identified to avoid adverse consequences.

[0037] In one or more embodiments of the present specification, the user can operate the client to select the virtual fraud scenario that he wants to test. Figure 2As shown, step S102 may include the following steps S102-2 and S102-4:

[0038] Step S102-2, receiving a first test request sent by the client; wherein the first test request includes target situation information selected by the user to be tested from situation information of multiple virtual fraud situations displayed by the client;

[0039] Specifically, the client displays the context information of multiple preset virtual fraud scenarios in response to the start-up operation of the user to be tested, or obtains and displays the context information of each current virtual fraud scenario from the server; and obtains the target context information selected by the user to be tested, and sends a first test request to the server according to the target context information. The context information may be one or more of the context name, context identifier, corresponding fraud mode, and other information. The first test request may also include user information of the user to be tested, such as user name, contact information, etc. The user information is obtained by the client in response to the test operation of the user to be tested (such as clicking the test button, etc.).

[0040] Step S102 - 4 , determining the virtual fraud scenario corresponding to the target scenario information as the target virtual fraud scenario that matches the user to be tested.

[0041] Corresponding to step S102-2 and step S102-4, as shown in Figure 2 As shown, step S104 may include the following steps S104-2 and S104-4, and step S106 may include the following steps S106-2:

[0042] Step S104-2, acquiring corresponding scenario construction data according to the scenario information of the target virtual fraud scenario;

[0043] Specifically, the target situation information in the first test request is determined as the situation information of the target virtual fraud situation; based on the situation information, the associated situation construction data is obtained from the association relationship between the pre-established situation information and the situation construction data, and the obtained situation construction data is determined as the situation construction data of the target virtual fraud situation.

[0044] Step S104-4, sending the scenario construction data to the client, so that the client displays the target virtual fraud scenario according to the scenario construction data, and obtains the behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario;

[0045] Step S106-2: receiving behavior data sent by the client.

[0046] Therefore, when the user to be tested is interested in the target virtual fraud scenario, the client can be operated to send a first test request to the server, thereby performing anti-fraud test processing based on the target virtual fraud scenario displayed by the client, which can meet the test needs of the user to be tested.

[0047] Considering that in actual applications, there are some users who want to conduct anti-fraud testing, but because there are multiple virtual fraud scenarios, they do not know which one is more suitable for them and do not know how to choose. Based on this, in one or more embodiments of this specification, suitable virtual fraud scenarios can also be recommended to the users to be tested based on intelligent analysis. Specifically, Figure 3 As shown, step S102 may include the following steps S102-6 to S102-10:

[0048] Step S102-6, receiving a second test request sent by the client, and acquiring characteristic data of the user to be tested according to the user information in the second test request;

[0049] Specifically, the client obtains user information provided by the user to be tested in response to the test operation of the user to be tested; and sends a second test request to the server according to the obtained user information. The server obtains the user information from the second test request, and obtains the characteristic data of the user to be tested from a specified location according to the user information. The characteristic data may include one or more of payment records, online shopping records, social information, and the like; and the social information may include contact information, chat records, and the like.

[0050] In order to ensure the security of the characteristic data of the user to be tested, in one or more embodiments of this specification, before obtaining the characteristic data of the user to be tested from the specified location according to the user information, it may also include: sending authorization request data to the client; the client displays the authorization prompt information according to the received authorization request data, and when obtaining the authorization confirmation information of the authorization confirmation operation performed by the user to be tested based on the authorization prompt information, the authorization confirmation information is sent to the server. When the server receives the authorization confirmation information, it obtains the associated data from the specified database or specified device according to the user information, and determines the obtained data as the characteristic data of the user to be tested.

[0051] Step S102-8, using a pre-trained analysis model to analyze and process the acquired feature data to obtain the target preference of the user to be tested;

[0052] Specifically, considering that the user's characteristic data can reflect the user's behavior and preferences, for example, the payment record can reflect whether the user has transferred money to a specific account; the online shopping record can reflect whether the user has the habit of online shopping and brushing orders; social information can reflect the user's social group, as well as the main chat topics between the user and the social group. Based on this, in one or more embodiments of this specification, the characteristic data of multiple users are collected in advance, and training and processing are performed based on the collected characteristic data to obtain an analysis model. When the server obtains the characteristic data of the user to be tested, the obtained characteristic data is input into the pre-trained analysis model, and the characteristic data is analyzed and processed by the analysis model to obtain the target preference of the user to be tested. Among them, the training method of the analysis model can refer to the existing model training method, and this specification does not make specific limitations on this. The user's preferences include but are not limited to online shopping and brushing orders, gambling, playing games, naked chatting, etc.

[0053] Step S102 - 10 , determining a virtual fraud scenario that matches the target preference among the plurality of pre-constructed virtual fraud scenarios as a target virtual fraud scenario that matches the user to be tested.

[0054] Optionally, an association relationship between user preferences and virtual fraud scenarios is established in advance, and accordingly, step S102-10 may include: according to the target preference, obtaining an associated virtual fraud scenario from the association relationship between the user preference and the virtual fraud scenario, and determining the obtained virtual fraud scenario as a target virtual fraud scenario that matches the user to be tested. Alternatively, an association relationship between user preferences and fraud patterns, and an association relationship between fraud patterns and virtual fraud scenarios are established in advance; accordingly, step S102-10 may include: according to the target preference, obtaining an associated target fraud pattern from the association relationship between the user preference and the fraud pattern; according to the target fraud pattern, obtaining an associated virtual fraud scenario from the association relationship between the fraud pattern and the virtual fraud scenario, and determining the obtained virtual fraud scenario as a target virtual fraud scenario that matches the user to be tested. The method for determining the target virtual fraud scenario is not limited to the above method, and can be set as needed in actual applications.

[0055] Further, corresponding to the above steps S102-6 to S106-10, as Figure 3As shown, step S104 may include the aforementioned step S104-2 and step S104-4, and step S106 may include the aforementioned step S106-2. The repetitive parts are not repeated here. In particular, in step S104-2, the corresponding scenario construction data is obtained according to the scenario information of the target virtual fraud scenario. After determining the target virtual fraud scenario, according to the preset scenario information of the target virtual fraud scenario, the associated scenario construction data is obtained from the association relationship between the pre-established scenario information and the scenario construction data, and the acquired scenario construction data is determined as the scenario construction data of the target virtual fraud scenario.

[0056] Thus, when the server receives the second test request sent by the client, it analyzes and processes the acquired characteristic data of the user to be tested based on the pre-trained analysis model to obtain the target preference of the user to be tested, and determines the target virtual fraud scenario that matches the user to be tested based on the target preference, so that the user to be tested performs anti-fraud test processing based on the target virtual fraud scenario, which can make the anti-fraud test closer to the actual situation of the user. For example, if the user to be tested prefers online shopping instead of gambling, the virtual fraud scenario corresponding to the online shopping fraud mode is determined as the target virtual fraud scenario that matches the user to be tested, instead of determining the virtual fraud scenario corresponding to the gambling fraud mode as the target virtual fraud scenario that matches the user to be tested, etc. Therefore, the anti-fraud test can be more helpful to the user to be tested, reducing the risk of the user to be tested being defrauded by the fraud mode corresponding to the target virtual fraud scenario.

[0057] In order to expand the scope of anti-fraud testing and enable more users to be aware of fraudulent means, in one or more embodiments of this specification, for a user group that has installed an anti-fraud test-related client in the terminal device and has registered the client, the server can also actively recommend matching target virtual fraud scenarios to the user. Figure 4 As shown, step S102 may include the following steps S102-12:

[0058] Step S102-12, if it is determined that among the multiple users corresponding to the multiple user information included in the designated information database, there is a user to be tested that meets the preset test condition, then a target virtual fraud scenario that matches the user to be tested among the multiple pre-constructed virtual fraud scenarios is determined;

[0059] Specifically, the method may also include: obtaining characteristic data of corresponding users according to multiple user information included in the designated information library; using a pre-trained analysis model to analyze and process the characteristic data of each user respectively to obtain the target preference of each user; matching the target preference with the preset preference; if it is determined that there is a successfully matched target preference, it is determined that there is a user to be tested that meets the preset test conditions, and the user corresponding to the successfully matched target preference is determined as the user to be tested. Among them, the designated information library includes user information of each user of the client that has registered for anti-fraud testing; the preset preference is a preference that matches the fraud mode corresponding to each virtual fraud scenario, such as online shopping, gambling, playing games, naked chatting, etc. The process of obtaining characteristic data and analyzing and processing the characteristic data of each user using a pre-trained analysis model can be found in the above-mentioned related description, and the repeated parts will not be repeated here.

[0060] Corresponding to step S102-12, Figure 4 As shown, step S104 may include the following steps S104-6 to S104-10: step S106 may include the aforementioned step S106-2.

[0061] Step S104-6, sending test prompt information to the client of the user to be tested according to the context information of the target virtual fraud context, so that the client displays the test prompt information, and when the user to be tested operates on the test prompt information, sending a data acquisition request to the server according to the context information;

[0062] The specific content of the test prompt information can be set according to actual needs in actual applications.

[0063] Step S104-8, if a data acquisition request sent by the client is received, then acquiring corresponding context construction data according to the context information in the data acquisition request;

[0064] Specifically, when the server receives the data acquisition request sent by the client, it obtains context information from the data acquisition request; based on the obtained context information, it obtains the associated context construction data from the pre-established association relationship between the context information and the context construction data.

[0065] Step S104 - 10 , sending the scenario construction data to the client, so that the client displays the target virtual fraud scenario according to the scenario construction data, and obtains the behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario.

[0066] In this embodiment, the server actively obtains the characteristic data of the corresponding user according to the multiple user information included in the designated information library, and when it is determined according to the characteristic data that there is a user to be tested that meets the preset test conditions, it sends a test prompt information to the client of the user to be tested according to the context information of the target virtual fraud context that matches the user to be tested, so as to prompt the user to be tested to perform the test process. In this way, the test can be promoted on a larger scale, so that more users can establish anti-fraud awareness, which has a promoting effect on both the asset security of the user's personal assets and the stability of society.

[0067] Based on any of the above embodiments, in order to let the user to be tested know the test result, in one or more embodiments of this specification, step S108 may also include: sending the test result to the client of the user to be tested, so that the client displays the test result.

[0068] In order to enhance the user's test experience and the fun of the test, in one or more embodiments of this specification, Figure 5 As shown, after step S108, the following steps S110 and S112 may also be included:

[0069] Step S110, if it is determined according to the test result that the fraud pattern in the target virtual fraud scenario has successfully defrauded the user to be tested, a preset penalty treatment is performed on the user to be tested;

[0070] Step S112: if it is determined according to the test result that the fraud pattern in the target virtual fraud scenario fails to defraud the user to be tested, a preset reward process is performed on the user to be tested.

[0071] Among them, the penalty processing may include deducting the points or virtual coins pre-allocated to the user to be tested, a virtual black screen, etc. The reward processing may include rewarding the user to be tested with points or virtual coins, rewarding the number of tests, etc. It should be pointed out that the methods of penalty processing and reward processing are not limited to the above methods, and can be set according to needs in actual applications.

[0072] Furthermore, in order to enable the user to be tested to have a clearer understanding of the fraudulent means in the target virtual fraud scenario, in one or more embodiments of this specification, Figure 6 As shown, after step S108, the following step S114 may also be included:

[0073] Step S114, revealing the fraudulent means in the target virtual fraud scenario to the user to be tested.

[0074] Specifically, the disclosure data of the fraudulent means in the target virtual fraud scenario is sent to the client of the user to be tested, so that the client can disclose the fraudulent means in the target virtual fraud scenario based on the disclosure data. The disclosure method of the fraudulent means may include disclosing the fraudulent means by text display, disclosing the fraudulent means by voice playback, etc.; it can be set according to the actual application. It should be noted that step S114 can also be performed after the aforementioned step S110, or after the aforementioned step S112.

[0075] On the basis of any of the above embodiments, in order to achieve a more immersive anti-fraud test for users, in one or more embodiments of this specification, before step S102, the following may also be included:

[0076] According to the obtained construction information of multiple virtual fraud scenarios, multiple corresponding virtual fraud scenarios are constructed, and scenario construction data of each virtual fraud scenario is generated. And the scenario construction data is associated with the scenario information of the corresponding virtual fraud scenario and saved. Among them, the construction information includes interface style information, human-computer interaction mode information, etc.

[0077] The above is a test processing method based on the server-side and client-side system architecture, which determines the target virtual fraud scenario that matches the user to be tested in a plurality of pre-constructed virtual fraud scenarios; performs display processing of the target virtual fraud scenario based on the scenario construction data of the target virtual fraud scenario, obtains the behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario, and generates the test results of the user to be tested based on the behavior data. Therefore, based on the target virtual fraud scenario that matches the user to be tested, the anti-fraud test processing is performed on the user to be tested, which allows the user to perform actual operations in it, giving the user a stronger sense of substitution and physical sensation, so that the user can more truly experience the fraudulent means, the urgency of time, the temptation of benefits or potential major losses, etc. It is conducive to the user to establish an effective method for identifying fraud, so that when encountering corresponding fraudulent means in real life, the risk can be quickly identified to avoid adverse consequences.

[0078] In order to establish user trust in anti-fraud testing and to be able to perform corresponding analysis and other processing based on the user's effective test results in the future, anti-fraud testing can also be performed based on the blockchain system. That is, based on the same technical concept as the test processing method described above, one or more embodiments of this specification also provide another test processing method, Figure 7 A flowchart of another test processing method provided for one or more embodiments of this specification, Figure 7 The method in can be applied to blockchain systems; e.g. Figure 7 As shown, the method may include the following steps:

[0079] Step S202, determining a target virtual fraud scenario that matches the user to be tested from among a plurality of pre-constructed virtual fraud scenarios;

[0080] Step S204, performing display processing of the target virtual fraud scenario according to the acquired scenario construction data of the target virtual fraud scenario;

[0081] Step S206, obtaining behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario;

[0082] Step S208, calling the smart contract in the blockchain system, generating the test results of the user to be tested based on the obtained behavior data based on the smart contract, and saving the test results in the blockchain system.

[0083] Among them, the implementation method of step S202 to step S206 is the same as the implementation method of the aforementioned step S102 to step S106, and the aforementioned related description can be referred to, and the repeated parts are not repeated here. In particular, in the aforementioned steps S102 to step S106, the server interacts with the client of the user to be tested; while in steps S202 to step S206, the blockchain node in the blockchain system interacts with the client of the user to be tested.

[0084] Optionally, in one or more embodiments of the present specification, the smart contract may include analysis rules for the behavior data corresponding to each virtual fraud scenario; accordingly, in step S208, based on the smart contract and the context information of the target virtual fraud scenario, the corresponding analysis rules are obtained; and, according to the obtained analysis rules, the behavior data is analyzed and processed, and the test results of the user to be tested are generated. Alternatively, each virtual fraud scenario may correspond to a smart contract, and the smart contract includes analysis rules for the behavior data of the corresponding virtual fraud scenario; accordingly, in step S208, according to the context information of the target virtual fraud scenario, the corresponding target smart contract is determined; the target smart contract is called, and the behavior data is analyzed and processed based on the analysis rules in the target smart contract, and the test results of the user to be tested are generated. Since smart contracts have the characteristics of automatic execution and user inability to intervene, generating test results based on smart contracts can not only improve the efficiency of generating test results, but also ensure the authenticity and validity of the test results.

[0085] Further, in order to facilitate the query of the test results, in one or more embodiments of the present specification, saving the test results to the blockchain system in step S208 may include: generating test record information according to the user information of the determined user to be tested, the test results, and the scenario information of the target virtual fraud scenario; saving the test record information to the blockchain system;

[0086] Correspondingly, the method may further include:

[0087] Receive a query request sent by a client of the user to be tested; query the corresponding test result from the blockchain system according to the query information of the test result to be queried included in the query request; and send the queried test result to the client.

[0088] Optionally, the query information may include user information, and accordingly, the blockchain node may query the test results of the corresponding user to be tested in each virtual fraud scenario that has been tested from the blockchain system based on the query information, and send the queried test results to the client of the user to be tested. Alternatively, the query information may include user information and scenario information, and accordingly, the blockchain node may query the test results of the corresponding user to be tested in the virtual fraud scenario corresponding to the scenario information in the query information from the blockchain system based on the query information, and send the queried test results to the client of the user to be tested.

[0089] Furthermore, in order to ensure the privacy security of the user to be tested, in one or more embodiments of this specification, generating test record information may include: encrypting the user information according to a preset encryption algorithm to obtain a ciphertext of the user information, and generating the test record information according to the ciphertext of the user information, the test result, and the scenario information of the target virtual fraud scenario. Correspondingly, when querying according to the query information, decrypting the ciphertext of the user information in the test record information according to a preset decryption algorithm to obtain the user information; and matching the obtained user information with the user information in the query information.

[0090] Furthermore, after step S208, the disclosure process of fraud means, reward and punishment process, etc. The specific implementation method can refer to the above related description, and the repeated parts will not be repeated here.

[0091] In one or more embodiments of the present specification, among the pre-constructed multiple virtual fraud scenarios, a target virtual fraud scenario matching the user to be tested is determined; based on the acquired scenario construction data of the target virtual fraud scenario, the target virtual fraud scenario is displayed and processed, and the behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario is obtained, and the test results of the user to be tested are generated based on the behavior data based on the smart contract, and the test results are saved in the blockchain system. Thus, based on the target virtual fraud scenario matching the user to be tested, the anti-fraud test processing is performed on the user to be tested, which allows the user to perform actual operations in it, giving the user a stronger sense of substitution and physical sensation, so that the user can more truly experience the fraudulent means, the urgency of time, the temptation of interests or potential major losses, etc. It is conducive to the user to establish an effective method for identifying fraud, so that when encountering corresponding fraudulent means in real life, the risk can be quickly identified to avoid adverse consequences. Generating test results based on smart contracts and saving them in the blockchain system can ensure the authenticity of the test and the validity of the test results based on the openness, transparency, and tamper-proof nature of the blockchain and the execution of smart contracts, which is conducive to building user trust and providing effective data basis for subsequent analysis of test results.

[0092] Corresponding to the above Figures 2 to 6 The test processing method described is based on the same technical concept, and one or more embodiments of this specification also provide a test processing device. Figure 8 A schematic diagram of the module composition of a test processing device provided in one or more embodiments of this specification, such as Figure 8 As shown, the device may include:

[0093] A determination module 301 determines a target virtual fraud scenario that matches the user to be tested from among a plurality of pre-constructed virtual fraud scenarios;

[0094] The processing module 302 performs display processing of the target virtual fraud scenario according to the acquired scenario construction data of the target virtual fraud scenario;

[0095] An acquisition module 303 is used to acquire behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario;

[0096] The generating module 304 generates the test result of the user to be tested according to the behavior data.

[0097] Optionally, the device further comprises: a punishment module and a reward module;

[0098] The penalty module performs a preset penalty on the user to be tested if it is determined according to the test result that the fraud pattern in the target virtual fraud scenario has successfully defrauded the user to be tested;

[0099] The reward module performs a preset reward process on the user to be tested if it is determined according to the test result that the fraud pattern in the target virtual fraud scenario fails to defraud the user to be tested.

[0100] Optionally, the device further comprises: a revealing module;

[0101] The disclosure module discloses the fraudulent means in the target virtual fraud scenario to the user to be tested.

[0102] The test processing device provided by one or more embodiments of this specification determines a target virtual fraud scenario that matches the user to be tested in a plurality of pre-constructed virtual fraud scenarios; performs display processing of the target virtual fraud scenario based on the scenario construction data of the acquired target virtual fraud scenario, and obtains the behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario, and generates the test result of the user to be tested based on the behavior data. Thus, based on the target virtual fraud scenario that matches the user to be tested, the anti-fraud test processing is performed on the user to be tested, which enables the user to perform actual operations in it, giving the user a stronger sense of substitution and physical sensation, and allowing the user to more truly experience the fraudulent means, the urgency of time, the temptation of benefits or potential major losses, etc. It is beneficial for the user to be tested to establish an effective method for identifying fraud, so that when encountering corresponding fraudulent means in real life, the risk can be quickly identified to avoid adverse consequences.

[0103] Furthermore, corresponding to the above Figure 7 The test processing method described is based on the same technical concept, and one or more embodiments of this specification also provide another test processing device. Fig. 9 A schematic diagram of the module composition of another test processing device provided in one or more embodiments of this specification, such as Fig. 9 As shown, the device comprises:

[0104] A determination module 401 determines a target virtual fraud scenario that matches the user to be tested from among a plurality of pre-constructed virtual fraud scenarios;

[0105] Processing module 402, performing display processing of the target virtual fraud scenario according to the acquired scenario construction data of the target virtual fraud scenario;

[0106] An acquisition module 403 is used to acquire behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario;

[0107] A generation module 404 calls a smart contract in the blockchain system, and generates a test result of the user to be tested according to the behavior data based on the smart contract;

[0108] The saving module 405 saves the test result to the blockchain system.

[0109] Optionally, the saving module 405 generates test record information according to the determined user information of the user to be tested, the test result and the scenario information of the target virtual fraud scenario; and saves the test record information in the blockchain system;

[0110] Accordingly, the system further comprises: a query module;

[0111] The query module receives a query request sent by a client of the user to be tested; and

[0112] According to the query information of the test result to be queried included in the query request, query the corresponding test result from the blockchain system;

[0113] The queried test result is sent to the client.

[0114] The test processing device provided by one or more embodiments of this specification determines a target virtual fraud scenario that matches the user to be tested in a plurality of pre-constructed virtual fraud scenarios; performs display processing of the target virtual fraud scenario based on the acquired scenario construction data of the target virtual fraud scenario, obtains the behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario, generates the test result of the user to be tested based on the behavior data based on the smart contract, and saves the test result to the blockchain system. Thus, based on the target virtual fraud scenario that matches the user to be tested, the user to be tested is subjected to anti-fraud test processing, which enables the user to perform actual operations therein, giving the user a stronger sense of immersion and physical sensation, and enabling the user to more truly experience the fraudulent means, the urgency of time, the temptation of benefits or potential major losses, etc. It is beneficial for the user to be tested to establish an effective method for identifying fraud, so that when encountering corresponding fraudulent means in real life, the risk can be quickly identified to avoid adverse consequences. Generating test results based on smart contracts and saving them in the blockchain system can ensure the authenticity of the test and the validity of the test results based on the openness, transparency, and tamper-proof nature of the blockchain and the execution of smart contracts, which is conducive to building user trust and providing effective data basis for subsequent analysis of test results.

[0115] It should be noted that the embodiments of the test processing device in this specification and the embodiments of the test processing method in this specification are based on the same inventive concept, so the specific implementation of this embodiment can refer to the implementation of the corresponding test processing method mentioned above, and the repeated parts will not be repeated.

[0116] Furthermore, corresponding to the above Figures 2 to 6The test processing method described is based on the same technical concept, and one or more embodiments of this specification also provide a test processing system. Fig.10 A schematic diagram of a test processing system provided in one or more embodiments of this specification is shown in FIG. Fig.10 As shown, the system includes: a server 501 and a client 502;

[0117] The server 501 determines a target virtual fraud scenario that matches the user to be tested among a plurality of pre-constructed virtual fraud scenarios; sends the acquired scenario construction data of the target virtual fraud scenario to the client 502 of the user to be tested, and receives the behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario sent by the client; generates a test result of the user to be tested according to the behavior data;

[0118] The client 502 displays the target virtual fraud scenario according to the scenario construction data received from the server 501 ; obtains behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario, and sends the behavior data to the server 501 .

[0119] Optionally, the client 502 displays the context information of the multiple virtual fraud contexts in response to the test operation of the user to be tested; sends a first test request to the server 501 according to the acquired target context information selected by the user to be tested;

[0120] The server 501 receives the first test request, and determines the virtual fraud scenario corresponding to the target scenario information included in the first test request as a target virtual fraud scenario that matches the user to be tested.

[0121] Optionally, the client 502 obtains user information of the user to be tested in response to a test operation of the user to be tested; and sends a second test request to the server 501 according to the user information;

[0122] The server 501 receives the second test request, obtains feature data of the user to be tested according to the user information included in the second test request; uses a pre-trained analysis model to analyze and process the feature data to obtain the target preference of the user to be tested; and determines the virtual fraud scenario that matches the target preference among multiple pre-constructed virtual fraud scenarios as the target virtual fraud scenario that matches the user to be tested.

[0123] Optionally, if the server 501 determines that there is a user to be tested that meets the preset test conditions among the multiple users corresponding to the multiple user information included in the designated information library, it determines a target virtual fraud scenario that matches the user to be tested among the multiple pre-constructed virtual fraud scenarios; sends a test prompt message to the client 502 of the user to be tested according to the scenario information of the target virtual fraud scenario; if a data acquisition request sent by the client 502 is received, the server 501 acquires corresponding scenario construction data according to the scenario information in the data acquisition request; sends the scenario construction data to the client 502, and receives the behavior data sent by the client 502;

[0124] The client 502 displays the received test prompt information, and if the operation of the user to be tested on the test prompt information is obtained, sends the data acquisition request to the server 501 according to the situation information in the test prompt information; displays the target virtual fraud situation according to the situation construction data received from the server 501, and obtains the behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud situation, and sends the behavior data to the server 501.

[0125] The test processing system provided by one or more embodiments of this specification determines a target virtual fraud scenario that matches the user to be tested in a plurality of pre-constructed virtual fraud scenarios; performs display processing of the target virtual fraud scenario based on the scenario construction data of the acquired target virtual fraud scenario, and obtains the behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario, and generates the test result of the user to be tested based on the behavior data. Thus, based on the target virtual fraud scenario that matches the user to be tested, the anti-fraud test processing is performed on the user to be tested, which enables the user to perform actual operations in it, giving the user a stronger sense of substitution and physical sensation, and allowing the user to more truly experience the fraudulent means, the urgency of time, the temptation of benefits or potential major losses, etc. It is beneficial for the user to be tested to establish an effective method for identifying fraud, so that when encountering corresponding fraudulent means in real life, the risk can be quickly identified to avoid adverse consequences.

[0126] Furthermore, corresponding to the above Figure 7 The test processing method described is based on the same technical concept, and one or more embodiments of this specification also provide a test processing system. Fig.11 A schematic diagram of a test processing system provided in one or more embodiments of this specification is shown in FIG. Fig.11 As shown, the system includes: a blockchain system 601 and a client 602;

[0127] The blockchain node in the blockchain system 601 determines a target virtual fraud scenario that matches the user to be tested among a plurality of pre-constructed virtual fraud scenarios; sends the acquired scenario construction data of the target virtual fraud scenario to the client 602 of the user to be tested, and receives the behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario sent by the client 602; calls the smart contract in the blockchain system 601, and generates a test result of the user to be tested based on the behavior data based on the smart contract; and saves the test result to the blockchain system 601;

[0128] The client 602 displays the target virtual fraud scenario according to the scenario construction data received and sent by the blockchain node; obtains behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario, and sends the behavior data to the blockchain node.

[0129] The test processing system provided by one or more embodiments of this specification determines a target virtual fraud scenario that matches the user to be tested in a plurality of pre-constructed virtual fraud scenarios; performs display processing of the target virtual fraud scenario based on the acquired scenario construction data of the target virtual fraud scenario, obtains the behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario, generates the test results of the user to be tested based on the behavior data based on the smart contract, and saves the test results to the blockchain system. Thus, based on the target virtual fraud scenario that matches the user to be tested, the user to be tested is subjected to anti-fraud test processing, which enables the user to perform actual operations therein, giving the user a stronger sense of immersion and physical sensation, and enabling the user to more truly experience the fraudulent means, the urgency of time, the temptation of benefits or potential significant losses, etc. It is beneficial for the user to be tested to establish an effective method for identifying fraud, so that when encountering corresponding fraudulent means in real life, the risk can be quickly identified to avoid adverse consequences. Generating test results based on smart contracts and saving them in the blockchain system can ensure the authenticity of the test and the validity of the test results based on the openness, transparency, and tamper-proof nature of the blockchain and the execution of smart contracts, which is conducive to building user trust and providing effective data basis for subsequent analysis of test results.

[0130] It should be noted that the embodiments of the test processing system in this specification and the embodiments of the test processing method in this specification are based on the same inventive concept, so the specific implementation of this embodiment can refer to the implementation of the corresponding test processing method mentioned above, and the repeated parts will not be repeated.

[0131] Further, corresponding to the test processing method described above, based on the same technical concept, one or more embodiments of this specification also provide a test processing device, which is used to execute the test processing method described above. Fig.12 A schematic diagram of the structure of a test processing device provided for one or more embodiments of this specification.

[0132] like Fig.12 As shown, the test processing device may have relatively large differences due to different configurations or performances, and may include one or more processors 701 and memory 702, and the memory 702 may store one or more storage applications or data. Among them, the memory 702 may be a short-term storage or a persistent storage. The application stored in the memory 702 may include one or more modules (not shown in the figure), and each module may include a series of computer executable instructions in the test processing device. Furthermore, the processor 701 may be configured to communicate with the memory 702 to execute a series of computer executable instructions in the memory 702 on the test processing device. The test processing device may also include one or more power supplies 703, one or more wired or wireless network interfaces 704, one or more input and output interfaces 705, one or more keyboards 706, etc.

[0133] In a specific embodiment, the test processing device includes a memory and one or more programs, wherein the one or more programs are stored in the memory, and the one or more programs may include one or more modules, and each module may include a series of computer executable instructions for the test processing device, and the one or more programs configured to be executed by one or more processors include computer executable instructions for performing the following:

[0134] Determine a target virtual fraud scenario that matches the user to be tested from among a plurality of pre-constructed virtual fraud scenarios;

[0135] Performing display processing of the target virtual fraud scenario according to the acquired scenario construction data of the target virtual fraud scenario;

[0136] Acquiring behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario;

[0137] Generate a test result of the user to be tested according to the behavior data.

[0138] The test processing device provided by one or more embodiments of this specification determines a target virtual fraud scenario that matches the user to be tested in a plurality of pre-constructed virtual fraud scenarios; performs display processing of the target virtual fraud scenario based on the scenario construction data of the acquired target virtual fraud scenario, and obtains the behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario, and generates the test result of the user to be tested based on the behavior data. Thus, based on the target virtual fraud scenario that matches the user to be tested, the anti-fraud test processing is performed on the user to be tested, which enables the user to perform actual operations in it, giving the user a stronger sense of substitution and physical sensation, and allowing the user to more truly experience the fraudulent means, the urgency of time, the temptation of benefits or potential major losses, etc. It is beneficial for the user to be tested to establish an effective method for identifying fraud, so that when encountering corresponding fraudulent means in real life, the risk can be quickly identified to avoid adverse consequences.

[0139] In another specific embodiment, the test processing device includes a memory and one or more programs, wherein the one or more programs are stored in the memory, and the one or more programs may include one or more modules, and each module may include a series of computer executable instructions for the test processing device, and the one or more programs configured to be executed by one or more processors include computer executable instructions for performing the following:

[0140] Determine a target virtual fraud scenario that matches the user to be tested from among a plurality of pre-constructed virtual fraud scenarios;

[0141] Performing display processing of the target virtual fraud scenario according to the acquired scenario construction data of the target virtual fraud scenario;

[0142] Acquiring behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario;

[0143] Calling a smart contract in the blockchain system, and generating a test result of the user to be tested based on the smart contract and the behavior data;

[0144] The test results are saved in the blockchain system.

[0145] Optionally, when the computer executable instructions are executed, generating the test result of the user to be tested according to the behavior data includes:

[0146] The smart contract in the blockchain system is called, and the test result of the user to be tested is generated according to the behavior data based on the smart contract.

[0147] The test processing device provided by one or more embodiments of this specification determines a target virtual fraud scenario that matches the user to be tested in a plurality of pre-constructed virtual fraud scenarios; performs display processing of the target virtual fraud scenario based on the scenario construction data of the acquired target virtual fraud scenario, obtains the behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario, generates the test result of the user to be tested based on the behavior data based on the smart contract, and saves the test result to the blockchain system. Thus, based on the target virtual fraud scenario that matches the user to be tested, the anti-fraud test processing is performed on the user to be tested, which enables the user to perform actual operations in it, giving the user a stronger sense of substitution and physical sensation, so that the user can more truly experience the fraudulent means, the urgency of time, the temptation of interests or potential major losses, etc. It is conducive to the user to establish an effective method for identifying fraud, so that when encountering corresponding fraudulent means in real life, the risk can be quickly identified to avoid adverse consequences. Generating test results based on smart contracts and saving them in the blockchain system can ensure the authenticity of the test and the validity of the test results based on the openness, transparency, and tamper-proof nature of the blockchain and the execution of smart contracts, which is conducive to building user trust and providing effective data basis for subsequent analysis of test results.

[0148] It should be noted that the embodiments of the test processing equipment in this specification and the embodiments of the test processing method in this specification are based on the same inventive concept, so the specific implementation of this embodiment can refer to the implementation of the corresponding test processing method mentioned above, and the repeated parts will not be repeated.

[0149] Further, corresponding to the test processing method described above, based on the same technical concept, one or more embodiments of this specification further provide a storage medium for storing computer executable instructions. In a specific embodiment, the storage medium may be a USB flash drive, an optical disk, a hard disk, etc. When the computer executable instructions stored in the storage medium are executed by the processor, the following process can be implemented:

[0150] Determine a target virtual fraud scenario that matches the user to be tested from among a plurality of pre-constructed virtual fraud scenarios;

[0151] Performing display processing of the target virtual fraud scenario according to the acquired scenario construction data of the target virtual fraud scenario;

[0152] Acquiring behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario;

[0153] Generate a test result of the user to be tested according to the behavior data.

[0154] The computer executable instructions stored in the storage medium provided in one or more embodiments of this specification are executed by the processor, by determining the target virtual fraud scenario that matches the user to be tested in a plurality of pre-constructed virtual fraud scenarios; performing display processing of the target virtual fraud scenario according to the acquired scenario construction data of the target virtual fraud scenario, and obtaining the behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario, and generating the test result of the user to be tested according to the behavior data. Thus, based on the target virtual fraud scenario that matches the user to be tested, the anti-fraud test processing is performed on the user to be tested, which enables the user to perform actual operations in it, giving the user a stronger sense of substitution and physical sensation, so that the user can more truly experience the fraudulent means, the urgency of time, the temptation of benefits or potential major losses, etc. It is conducive to the user to establish an effective method for identifying fraud, so that when encountering corresponding fraudulent means in real life, the risk can be quickly identified to avoid adverse consequences.

[0155] In another specific embodiment, the storage medium may be a USB flash drive, an optical disk, a hard disk, etc. When the computer executable instructions stored in the storage medium are executed by the processor, the following process can be implemented:

[0156] Determine a target virtual fraud scenario that matches the user to be tested from among a plurality of pre-constructed virtual fraud scenarios;

[0157] Performing display processing of the target virtual fraud scenario according to the acquired scenario construction data of the target virtual fraud scenario;

[0158] Acquiring behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario;

[0159] Calling a smart contract in the blockchain system, and generating a test result of the user to be tested based on the smart contract and the behavior data;

[0160] The test results are saved in the blockchain system.

[0161] The computer executable instructions stored in the storage medium provided in one or more embodiments of this specification are executed by the processor, and in a plurality of pre-constructed virtual fraud scenarios, a target virtual fraud scenario matching the user to be tested is determined; according to the scenario construction data of the acquired target virtual fraud scenario, the display processing of the target virtual fraud scenario is performed, and the behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario is obtained, and the test results of the user to be tested are generated based on the behavior data based on the smart contract, and the test results are saved in the blockchain system. Thus, based on the target virtual fraud scenario matching the user to be tested, the anti-fraud test processing is performed on the user to be tested, which enables the user to perform actual operations in it, giving the user a stronger sense of substitution and physical sensation, so that the user can more truly experience the fraud means, the urgency of time, the temptation of interests or potential major losses, etc. It is conducive to the user to establish an effective method for identifying fraud, so that when encountering corresponding fraud means in real life, the risk can be quickly identified to avoid adverse consequences. Generating test results based on smart contracts and saving them in the blockchain system can ensure the authenticity of the test and the validity of the test results based on the openness, transparency, and tamper-proof nature of the blockchain and the execution of smart contracts, which is conducive to building user trust and providing effective data basis for subsequent analysis of test results.

[0162] It should be noted that the embodiments of the storage medium in this specification and the embodiments of the test processing method in this specification are based on the same inventive concept, so the specific implementation of this embodiment can refer to the implementation of the corresponding test processing method mentioned above, and the repeated parts will not be repeated.

[0163] The above is a description of a specific embodiment of the 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.

[0164] In the 1990s, improvements to a technology could be clearly distinguished as hardware improvements (for example, improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the method flow). However, with the development of technology, many improvements to the method flow today can be regarded as direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that an improvement in a method flow cannot be implemented using a hardware entity module. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is such an integrated circuit whose logical function is determined by the user's programming of the device. Designers can "integrate" a digital system on a PLD by programming it themselves, without having to ask a chip manufacturer to design and produce a dedicated integrated circuit chip. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly implemented by "logic compiler" software, which is similar to the software compiler used when developing and writing programs, and the original code before compilation must also be written in a specific programming language, which is called hardware description language (HDL). There is not only one HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also know that it is only necessary to program the method flow slightly in the above-mentioned hardware description languages ​​and program it into the integrated circuit, and then it is easy to obtain the hardware circuit that implements the logic method flow.

[0165] The controller can be implemented in any appropriate manner, for example, the controller can take the form of a microprocessor or processor and a computer-readable medium storing a computer-readable program code (such as software or firmware) that can be executed by the (micro)processor, a logic gate, a switch, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller. Examples of controllers include, but are not limited to, the following microcontrollers: ARC625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. The memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art also know that in addition to implementing the controller in a purely computer-readable program code manner, the controller can be implemented in the form of a logic gate, a switch, an application-specific integrated circuit, a programmable logic controller, and an embedded microcontroller by logically programming the method steps. Therefore, this controller can be considered as a hardware component, and the devices included therein for implementing various functions can also be regarded as structures within the hardware component. Or even, the devices for implementing various functions can be regarded as both software modules for implementing the method and structures within the hardware component.

[0166] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0167] For the convenience of description, the above devices are described in terms of functions and are divided into various units. Of course, when implementing the embodiments of this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0168] It should be understood by those skilled in the art that one or more embodiments of this specification may be provided as a method, system or computer program product. Therefore, one or more embodiments of this specification may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0169] This specification is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of this specification. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0170] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0171] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0172] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0173] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0174] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0175] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0176] One or more embodiments of the present specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. One or more embodiments of the present specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0177] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0178] The above description is only an embodiment of this document and is not intended to limit this document. For those skilled in the art, this document may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this document should be included in the scope of the claims of this document.

Claims

1. A test processing method, used on a server, comprising: Determine a target virtual fraud scenario that matches a user to be tested from among a plurality of pre-constructed virtual fraud scenarios, wherein the user to be tested includes a user determined by matching a target preference corresponding to feature data of a plurality of users in a designated information library with a preset preference, wherein the designated information library includes user information of each user of a client that has registered for anti-fraud testing, and the preset preference is a preference that matches a fraud pattern corresponding to each virtual fraud scenario, and the process of determining the user to be tested includes: matching the target preference with the preset preference, and if it is determined that there is a successfully matched target preference, then determining that there is a user to be tested that meets the preset test condition, and determining the user corresponding to the successfully matched target preference as the user to be tested; Performing display processing of the target virtual fraud scenario according to the acquired scenario construction data of the target virtual fraud scenario; Acquiring behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario; Generate a test result of the user to be tested according to the behavior data.

2. The method according to claim 1, wherein determining a target virtual fraud scenario that matches the user to be tested from among the plurality of pre-constructed virtual fraud scenarios comprises: Receiving a first test request sent by a client; wherein the first test request includes target situation information selected by the user to be tested from situation information of multiple virtual fraud situations displayed by the client; The virtual fraud scenario corresponding to the target scenario information is determined as a target virtual fraud scenario that matches the user to be tested.

3. The method according to claim 1, wherein determining a target virtual fraud scenario that matches the user to be tested from among the plurality of pre-constructed virtual fraud scenarios comprises: Receive a second test request sent by the client; wherein the second test request includes user information of the user to be tested; Acquire characteristic data of the user to be tested according to the user information; Using a pre-trained analysis model to analyze and process the feature data to obtain the target preference of the user to be tested; A virtual fraud scenario that matches the target preference among a plurality of pre-constructed virtual fraud scenarios is determined as a target virtual fraud scenario that matches the user to be tested.

4. The method according to claim 2 or 3, wherein the display processing of the target virtual fraud scenario is performed based on the acquired scenario construction data of the target virtual fraud scenario, comprising: According to the situation information of the target virtual fraud situation, obtaining corresponding situation construction data; Sending the scenario construction data to the client, so that the client displays the target virtual fraud scenario according to the scenario construction data, and obtains behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario; The obtaining of behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario includes: The behavior data sent by the client is received.

5. The method according to claim 1, wherein determining a target virtual fraud scenario that matches the user to be tested from among a plurality of pre-constructed virtual fraud scenarios comprises: If it is determined that among the multiple users corresponding to the multiple user information included in the designated information database, there is a user to be tested that meets the preset test conditions, then a target virtual fraud scenario that matches the user to be tested among the multiple pre-constructed virtual fraud scenarios is determined; The step of performing display processing of the target virtual fraud scenario according to the acquired scenario construction data of the target virtual fraud scenario includes: Sending test prompt information to the client of the user to be tested according to the context information of the target virtual fraud context, so that the client displays the test prompt information, and when obtaining the operation of the user to be tested on the test prompt information, sending a data acquisition request to the server according to the context information; If the data acquisition request sent by the client is received, then acquiring corresponding context construction data according to the context information in the data acquisition request; Sending the scenario construction data to the client, so that the client displays the target virtual fraud scenario according to the scenario construction data, and obtains behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario; The obtaining of behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario includes: The behavior data sent by the client is received.

6. The method according to claim 5, further comprising: Acquire characteristic data of corresponding users according to the multiple user information included in the designated information database; Using a pre-trained analysis model to analyze and process the characteristic data of each user respectively to obtain the target preference of each user; Matching the target preference with the preset preference; If it is determined that there is a successfully matched target preference, it is determined that there is a user to be tested who meets the preset test condition, and the user corresponding to the successfully matched target preference is determined as the user to be tested.

7. The method according to claim 1, after generating the test result of the user to be tested according to the behavior data, further comprising: If it is determined according to the test result that the fraud pattern in the target virtual fraud scenario has successfully defrauded the user to be tested, a preset penalty is imposed on the user to be tested; If it is determined according to the test result that the fraud pattern in the target virtual fraud scenario fails to defraud the user to be tested, a preset reward processing is performed on the user to be tested.

8. The method according to claim 1, after generating the test result of the user to be tested according to the behavior data, further comprising: The fraudulent means in the target virtual fraud scenario are disclosed to the user to be tested.

9. The method according to claim 1, before determining a target virtual fraud scenario that matches the user to be tested among a plurality of pre-constructed virtual fraud scenarios, further comprising: According to the acquired construction information of the multiple virtual fraud scenarios, a corresponding multiple virtual fraud scenarios are constructed, and the scenario construction data of each virtual fraud scenario is generated.

10. A test processing method, used on a server, comprising: Determine a target virtual fraud scenario that matches a user to be tested from among a plurality of pre-constructed virtual fraud scenarios, wherein the user to be tested includes a user determined by matching a target preference corresponding to feature data of a plurality of users in a designated information library with a preset preference, wherein the designated information library includes user information of each user of a client that has registered for anti-fraud testing, and the preset preference is a preference that matches a fraud pattern corresponding to each virtual fraud scenario, and the process of determining the user to be tested includes: matching the target preference with the preset preference, and if it is determined that there is a successfully matched target preference, then determining that there is a user to be tested that meets the preset test condition, and determining the user corresponding to the successfully matched target preference as the user to be tested; Performing display processing of the target virtual fraud scenario according to the acquired scenario construction data of the target virtual fraud scenario; Acquiring behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario; Calling a smart contract in the blockchain system, and generating a test result of the user to be tested based on the smart contract and the behavior data; The test results are saved in the blockchain system.

11. The method according to claim 10, wherein the step of storing the test result in a blockchain system comprises: Generate test record information according to the determined user information of the user to be tested, the test result and the scenario information of the target virtual fraud scenario; Saving the test record information in the blockchain system; The method further comprises: Receiving a query request sent by a client of the user to be tested; According to the query information of the test result to be queried included in the query request, query the corresponding test result from the blockchain system; The queried test result is sent to the client.

12. A test processing device, used at a server, comprising: A determination module determines a target virtual fraud scenario that matches a user to be tested from among a plurality of pre-constructed virtual fraud scenarios, wherein the user to be tested includes a user determined by matching a target preference corresponding to feature data of a plurality of users in a designated information library with a preset preference, wherein the designated information library includes user information of each user of a client that has registered for anti-fraud testing, and the preset preference is a preference that matches a fraud pattern corresponding to each virtual fraud scenario, and the process of determining the user to be tested includes: matching the target preference with the preset preference, and if it is determined that there is a successfully matched target preference, then determining that there is a user to be tested that meets the preset test conditions, and determining the user corresponding to the successfully matched target preference as the user to be tested; A processing module, performing display processing of the target virtual fraud scenario according to the acquired scenario construction data of the target virtual fraud scenario; An acquisition module is used to acquire behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario; A generating module generates a test result of the user to be tested according to the behavior data.

13. A test processing device, used at a server, comprising: A determination module determines a target virtual fraud scenario that matches a user to be tested from among a plurality of pre-constructed virtual fraud scenarios, wherein the user to be tested includes a user determined by matching a target preference corresponding to feature data of a plurality of users in a designated information library with a preset preference, wherein the designated information library includes user information of each user of a client that has registered for anti-fraud testing, and the preset preference is a preference that matches a fraud pattern corresponding to each virtual fraud scenario, and the process of determining the user to be tested includes: matching the target preference with the preset preference, and if it is determined that there is a successfully matched target preference, then determining that there is a user to be tested that meets the preset test conditions, and determining the user corresponding to the successfully matched target preference as the user to be tested; A processing module, performing display processing of the target virtual fraud scenario according to the acquired scenario construction data of the target virtual fraud scenario; An acquisition module is used to acquire behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario; A generation module, calling a smart contract in the blockchain system, and generating a test result of the user to be tested according to the behavior data based on the smart contract; A saving module saves the test result to the blockchain system.

14. A test processing system comprising: Server and client; The server determines a target virtual fraud scenario that matches a user to be tested from among a plurality of pre-constructed virtual fraud scenarios, wherein the user to be tested includes a user determined by matching a target preference corresponding to feature data of a plurality of users in a designated information base with a preset preference, wherein the designated information base includes user information of each user of a client that has registered for anti-fraud testing, and the preset preference is a preference that matches a fraud pattern corresponding to each virtual fraud scenario. The process of determining the user to be tested includes: matching the target preference with the preset preference, and if it is determined that there is a successfully matched target preference, determining that there is a user to be tested that meets the preset test conditions, and determining the user corresponding to the successfully matched target preference as the user to be tested; sending the acquired scenario construction data of the target virtual fraud scenario to the client of the user to be tested, and receiving the behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario sent by the client; and generating a test result of the user to be tested according to the behavior data; The client displays the target virtual fraud scenario according to the scenario construction data received from the server; obtains behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario, and sends the behavior data to the server.

15. The system according to claim 14, The client, in response to the test operation of the user to be tested, displays the context information of the multiple virtual fraud contexts; and sends a first test request to the server according to the acquired target context information selected by the user to be tested; The server receives the first test request, and determines the virtual fraud scenario corresponding to the target scenario information included in the first test request as a target virtual fraud scenario that matches the user to be tested.

16. The system according to claim 14, The client, in response to the test operation of the user to be tested, obtains user information of the user to be tested; and sends a second test request to the server according to the user information; The server receives the second test request, obtains feature data of the user to be tested according to the user information included in the second test request, and uses a pre-trained analysis model to analyze and process the feature data to obtain a target preference of the user to be tested; A virtual fraud scenario that matches the target preference among a plurality of pre-constructed virtual fraud scenarios is determined as a target virtual fraud scenario that matches the user to be tested.

17. The system according to claim 14, The server determines a target virtual fraud scenario that matches the user to be tested from among the multiple virtual fraud scenarios that are pre-constructed, if it is determined that there is a user to be tested that meets the preset test conditions among the multiple users corresponding to the multiple user information included in the designated information database; Sending test prompt information to the client of the user to be tested according to the context information of the target virtual fraud context; If a data acquisition request sent by the client is received, then corresponding context construction data is acquired according to the context information in the data acquisition request; the context construction data is sent to the client, and the behavior data sent by the client is received; The client displays the received test prompt information, and if the operation of the user to be tested on the test prompt information is obtained, the data acquisition request is sent to the server according to the situation information in the test prompt information; the target virtual fraud situation is displayed according to the situation construction data received from the server, and the behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud situation is obtained, and the behavior data is sent to the server.

18. A test processing system comprising: Blockchain system and client; The blockchain node in the blockchain system determines a target virtual fraud scenario that matches a user to be tested among a plurality of pre-constructed virtual fraud scenarios, wherein the user to be tested includes a user determined by matching a target preference corresponding to feature data of a plurality of users in a designated information library with a preset preference, wherein the designated information library includes user information of each user of a client that has registered for anti-fraud testing, and the preset preference is a preference that matches a fraud pattern corresponding to each virtual fraud scenario. The process of determining the user to be tested includes: matching the target preference with the preset preference, and if it is determined that there is a successfully matched target preference, determining that there is a user to be tested that meets the preset test conditions, and determining the user corresponding to the successfully matched target preference as the user to be tested; sending the acquired scenario construction data of the target virtual fraud scenario to the client of the user to be tested, and receiving the behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario sent by the client; calling a smart contract in the blockchain system, and generating a test result of the user to be tested based on the behavior data based on the smart contract; and saving the test result to the blockchain system; The client displays the target virtual fraud scenario according to the received scenario construction data sent by the blockchain node; obtains the behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario, and sends the behavior data to the blockchain node.

19. A data processing device, used at a server, comprising: processor; as well as, a memory arranged to store computer executable instructions which, when executed, cause the processor to: Determine a target virtual fraud scenario that matches a user to be tested from among a plurality of pre-constructed virtual fraud scenarios, wherein the user to be tested includes a user determined by matching a target preference corresponding to feature data of a plurality of users in a designated information library with a preset preference, wherein the designated information library includes user information of each user of a client that has registered for anti-fraud testing, and the preset preference is a preference that matches a fraud pattern corresponding to each virtual fraud scenario, and the process of determining the user to be tested includes: matching the target preference with the preset preference, and if it is determined that there is a successfully matched target preference, then determining that there is a user to be tested that meets the preset test condition, and determining the user corresponding to the successfully matched target preference as the user to be tested; Performing display processing of the target virtual fraud scenario according to the acquired scenario construction data of the target virtual fraud scenario; Acquiring behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario; Generate a test result of the user to be tested according to the behavior data.

20. A data processing device, used at a server, comprising: processor; as well as, a memory arranged to store computer executable instructions which, when executed, cause the processor to: Determine a target virtual fraud scenario that matches a user to be tested from among a plurality of pre-constructed virtual fraud scenarios, wherein the user to be tested includes a user determined by matching a target preference corresponding to feature data of a plurality of users in a designated information library with a preset preference, wherein the designated information library includes user information of each user of a client that has registered for anti-fraud testing, and the preset preference is a preference that matches a fraud pattern corresponding to each virtual fraud scenario, and the process of determining the user to be tested includes: matching the target preference with the preset preference, and if it is determined that there is a successfully matched target preference, then determining that there is a user to be tested that meets the preset test condition, and determining the user corresponding to the successfully matched target preference as the user to be tested; Performing display processing of the target virtual fraud scenario according to the acquired scenario construction data of the target virtual fraud scenario; Acquiring behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario; Calling a smart contract in the blockchain system, and generating a test result of the user to be tested based on the smart contract and the behavior data; The test results are saved in the blockchain system.

21. A storage medium for storing computer executable instructions, for use at a server, wherein the computer executable instructions implement the following process when executed by a processor: Determine a target virtual fraud scenario that matches a user to be tested from among a plurality of pre-constructed virtual fraud scenarios, wherein the user to be tested includes a user determined by matching target preferences corresponding to feature data of a plurality of users in a designated information database with preset preferences, wherein the designated information database includes user information of each user of a client that has registered for anti-fraud testing, and the preset preferences are preferences that match fraud patterns corresponding to each virtual fraud scenario, and the process of determining the user to be tested includes: Matching the target preference with the preset preference, if it is determined that there is a successfully matched target preference, determining that there is a user to be tested that meets the preset test condition, and determining the user corresponding to the successfully matched target preference as the user to be tested; Performing display processing of the target virtual fraud scenario according to the acquired scenario construction data of the target virtual fraud scenario; Acquiring behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario; Generate a test result of the user to be tested according to the behavior data.

22. A storage medium for storing computer executable instructions, for use at a server, wherein the computer executable instructions implement the following process when executed by a processor: Determine a target virtual fraud scenario that matches a user to be tested from among a plurality of pre-constructed virtual fraud scenarios, wherein the user to be tested includes a user determined by matching target preferences corresponding to feature data of a plurality of users in a designated information database with preset preferences, wherein the designated information database includes user information of each user of a client that has registered for anti-fraud testing, and the preset preferences are preferences that match fraud patterns corresponding to each virtual fraud scenario, and the process of determining the user to be tested includes: Matching the target preference with the preset preference, if it is determined that there is a successfully matched target preference, determining that there is a user to be tested that meets the preset test condition, and determining the user corresponding to the successfully matched target preference as the user to be tested; Performing display processing of the target virtual fraud scenario according to the acquired scenario construction data of the target virtual fraud scenario; Acquiring behavior data corresponding to the operation behavior of the user to be tested in the target virtual fraud scenario; Calling a smart contract in the blockchain system, and generating a test result of the user to be tested based on the smart contract and the behavior data; The test results are saved in the blockchain system.

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