Security detection method and device for online incentive service issuing

Abstract

The invention relates to the technical field of intelligent decision making, is suitable for the field of personal and property guarantee services, and provides a safety detection method and device for online incentive service issuance, and the method comprises the steps: determining a second participating user meeting a first preset safety rule from first participating users of an application link of online incentive service; randomly selecting a third participating user from the second participating users in the extraction link; determining the risk degree of the third participating user based on the individual feature information of the third participating user, the activity configuration information of the online incentive service and a preset user risk assessment model; and if the risk degree is within the preset security risk range, reserving the third participating user in the accepted object set of the online incentive service, and otherwise, deleting the third participating user. According to the technical scheme, the user experience of the extraction activity of the online incentive service can be improved, and a positive contribution is made for popularization of personal guarantee service or property guarantee service.

Description

[Technical field]

[0001] The present application relates to the field of intelligent decision-making technology, is applicable to the field of personal and property protection services, and in particular, to a security detection method and device for the issuance of online incentive services. [Background technology]

[0002] With the rapid development of the Internet, in personal and property protection services, traditional offline marketing activities have gradually shifted to online. Users do not need to go to the site, but can directly enter the activity interface of the online incentive service through the client APP or mini program. After entering the activity interface, you can register for the online incentive service by registering a client account to obtain prizes such as red envelopes and vouchers. In this way, the onlineization of activities breaks the geographical restrictions, provides a convenient channel for users to participate in activities, and brings more traffic to major platforms.

[0003] However, the online incentive service draw activities also attracted a large number of abnormal users who were looking to get the wool. These abnormal users registered a large number of platform accounts through machine registration, manual registration and other means, and maintained platform activity by improving account information, real-name authentication, and increasing normal user behavior of accounts, thereby increasing user weight and concealing their identities. Then, by frequently participating in the online incentive service draw activities, they obtained a large number of platform red envelopes, coupons, vouchers and other prizes for arbitrage. This not only did not bring normal traffic users to the activity platform, but caused huge economic losses to it, and also accumulated the profit space of normal traffic users.

[0004] In this regard, the relevant technology generally limits the right to participate in activities and win prizes by monitoring the number of times the same IP and device number participate in activities, the frequency of support, the frequency of group purchase, etc. However, the accuracy of abnormal user identification in this way is low, and it is easy to misjudge normal traffic users as abnormal users, resulting in a poor user experience and poor activity effect.

[0005] Therefore, how to effectively identify normal users and abnormal users in the process of issuing online incentive services has become a technical problem that needs to be solved urgently. [Summary of the invention]

[0006] The embodiments of the present application provide a security detection method and device for the issuance of online incentive services, aiming to solve the technical problem of insufficient accuracy in the method of identifying abnormal users in the process of issuing online incentive services in the related art.

[0007] In a first aspect, an embodiment of the present application provides a security detection method for issuing online incentive services, including:

[0008] Determine a second participating user who meets the first preset safety rule from among the first participating users obtained in the registration phase of the online incentive service, wherein the online incentive service is a service content related to the personal protection service or the property protection service for a target customer group of the personal protection service or the property protection service;

[0009] Initiating a drawing phase of the online incentive service for the second participating user;

[0010] In the extraction phase, a specified number of third participating users are randomly selected from the second participating users as recipients of the online incentive service, and enter a risk assessment phase;

[0011] In the risk assessment phase, based on the individual characteristic information of the third participating user and the activity configuration information of the online incentive service, the input information of the preset user risk assessment model is determined;

[0012] Based on the input information, the preset user risk assessment model outputs the risk level of the third participating user, wherein the preset user risk assessment model is used to reflect the correlation between the input information and the risk level of the third participating user, and the risk level indicates the possibility that the third participating user is not a legal transferee;

[0013] If the risk level is within a preset security risk range, the third participating user is retained in the set of transferees of the online incentive service; otherwise, the third participating user is deleted from the set of transferees of the online incentive service.

[0014] In one embodiment of the present application, optionally, before the registration phase of the online incentive service is started, the process further includes:

[0015] Acquire activity configuration information of the online incentive service, wherein the activity configuration information includes an activity review identifier, an activity flow, the distribution content of the online incentive service, the distribution time, and the effective time of the distribution content;

[0016] If the activity configuration information satisfies the second preset security rule, the registration phase of the online incentive service is initiated.

[0017] In one embodiment of the present application, optionally, determining a second participating user who meets a first preset safety rule from among the first participating users obtained in the registration phase of the online incentive service includes:

[0018] Detecting whether the first participating user obtained during the registration phase of the online incentive service is in a list of abnormal users;

[0019] If the first participating user is not in the abnormal user list, the first participating user is determined to be the second participating user.

[0020] In one embodiment of the present application, optionally, determining input information of a preset user risk assessment model based on the individual feature information of the third participating user and the activity configuration information of the online incentive service includes:

[0021] Determining the activity type of the online incentive service;

[0022] Information associated with the activity type is selected from the individual feature information of the third participating user and the activity configuration information of the online incentive service as input information of the preset user risk assessment model.

[0023] In one embodiment of the present application, optionally, before starting the registration phase of the online incentive service, the process further includes:

[0024] Associated individual characteristic information and activity configuration information are set for each activity type.

[0025] In one embodiment of the present application, optionally, after the risk assessment phase is completed, the following is further included:

[0026] Based on the assessment result of the risk assessment link, the activity risk value corresponding to the activity type is corrected.

[0027] In a second aspect, an embodiment of the present application provides a security detection device for issuing online incentive services, including:

[0028] A first security detection unit is used to determine a second participating user who meets a first preset security rule from among the first participating users obtained in the registration phase of the online incentive service, wherein the online incentive service is a service content related to the personal protection service or the property protection service for a target customer group of the personal protection service or the property protection service;

[0029] An extraction phase starting unit, used to start the extraction phase of the online incentive service for the second participating user;

[0030] a transferee extraction unit, configured to randomly select a specified number of third participating users from the second participating users as transferees of the online incentive service in the extraction phase, and enter a risk assessment phase;

[0031] a second security detection unit, for determining input information of a preset user risk assessment model in the risk assessment link based on the individual feature information of the third participating user and the activity configuration information of the online incentive service, and for causing the preset user risk assessment model to output the risk level of the third participating user based on the input information, wherein the preset user risk assessment model is used to reflect the correlation between the input information and the risk level of the third participating user, and the risk level indicates the possibility that the third participating user is not a legal transferee;

[0032] A first execution unit, configured to retain the third participating user in the set of transferees of the online incentive service if the risk level is within a preset security risk range;

[0033] The second execution unit is configured to delete the third participating user from the set of transferees of the online incentive service if the risk level is not within a preset security risk range.

[0034] In one embodiment of the present application, optionally, the device further includes:

[0035] An activity configuration information acquisition unit, used to acquire the activity configuration information of the online incentive service before the registration phase of the online incentive service is started, wherein the activity configuration information includes an activity review identifier, an activity flow, the distribution content of the online incentive service, the distribution time, and the effective time of the distribution content;

[0036] The third security detection unit is used to start the registration process of the online incentive service if the activity configuration information meets the second preset security rule.

[0037] In one embodiment of the present application, optionally, the first security detection unit is specifically used to: detect whether the first participating user obtained in the registration phase of the online incentive service is in the list of abnormal users, wherein if the first participating user is not in the list of abnormal users, determine that the first participating user is the second participating user.

[0038] In one embodiment of the present application, optionally, the second safety detection unit includes:

[0039] An input information determination unit is used to determine the activity type of the online incentive service, and select information associated with the activity type from the individual feature information of the third participating user and the activity configuration information of the online incentive service as input information of the preset user risk assessment model.

[0040] In one embodiment of the present application, optionally, the device further includes:

[0041] The pre-configuration unit is used to set the associated individual characteristic information and activity configuration information for each activity type before starting the registration phase of the online incentive service.

[0042] In one embodiment of the present application, optionally, the device further includes:

[0043] The activity type risk assessment unit is used to correct the activity risk value corresponding to the activity type based on the assessment result of the risk assessment link after the risk assessment link is completed.

[0044] In a third aspect, an embodiment of the present application provides a computer device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are configured to execute the method described in the first aspect above.

[0045] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are used to execute the method described in the first aspect above.

[0046] The above technical solution aims to solve the technical problem of insufficient accuracy in identifying abnormal users in the process of issuing online incentive services in related technologies. In the distribution activity of service content related to personal protection services or property protection services for the target customer group of personal protection services or property protection services, first, among the first participating users obtained in the registration stage, a second participating user who meets the first preset security rule is determined. The first preset security rule is used to reflect the minimum participation conditions that the identity of the participating users in the registration stage of the online incentive service must meet.

[0047] At this point, the online incentive service extraction phase for the second participating user can be started. After eliminating the abnormal traffic users, the remaining second participating users can enter the online incentive service extraction phase. In the extraction phase, a specified number of third participating users can be randomly selected from all the second participating users through the random number extraction function. The specified number is the number of online incentive services that can be issued.

[0048] Next, in the risk assessment link, based on the individual characteristic information of the third participating user and the activity configuration information of the online incentive service, the input information of the preset user risk assessment model is determined, and then based on the input information, the preset user risk assessment model outputs the risk level of the third participating user.

[0049] Among them, the individual characteristic information of the third participating user and the activity configuration information of the online incentive service both reflect to a certain extent the possibility that the third participating user is an abnormal traffic user, and the risk level indicates the possibility that the third participating user is not a legal transferee, so the individual characteristic information of the third participating user and the activity configuration information of the online incentive service are correlated with the risk level of the third participating user. It should be supplemented that before the start of the activity, the individual characteristic information of the third participating user and the activity configuration information of the online incentive service in the historical online incentive service distribution activities, as well as the classification of the third participating user (that is, whether the third participating user is identified as an abnormal traffic user and excluded) can be obtained as a training set to train the preset user risk assessment model. It can be said that the preset user risk assessment model is used to reflect the correlation between the input information and the risk level of the third participating user.

[0050] Finally, if the risk level is within the preset security risk range, it can be determined that the third participating user is not an abnormal traffic user. At this time, the third participating user can be retained in the set of recipients of the online incentive service and the online incentive service can be issued to him.

[0051] On the contrary, if the risk level is not within the preset security risk range, it can be determined that the third participating user has the possibility of being an abnormal traffic user. At this time, in order to ensure the safe distribution of the online incentive service, the third participating user can be deleted from the set of recipients of the online incentive service.

[0052] The above technical solution can conduct a preliminary blacklist check on the participating users before the extraction of online incentive services, and then after the extraction, the risk level of the extracted participating users is assessed by the pre-trained preset user risk assessment model, and online incentive services are only issued to them when their risk level is within a safe range. Therefore, when extracting online incentive services for the target customer groups of personal protection services or property protection services, the security detection capabilities of participating users can be strengthened, and users who may have abnormal traffic can be automatically and timely eliminated to avoid online incentive services being obtained by abnormal traffic users and squeezing the legitimate profit space of the customer groups expected by personal protection services or property protection services. It can improve the user experience of online incentive service extraction activities and make positive contributions to the promotion of personal protection services or property protection services.

Brief Description of the Drawings

[0053] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0054] Figure 1 A flow chart showing a security detection method for online incentive service issuance according to an embodiment of the present application is shown;

[0055] Figure 2 A flow chart showing a security detection method for online incentive service issuance according to another embodiment of the present application is shown;

[0056] Figure 3 A block diagram of a computer device according to an embodiment of the present application is shown;

[0057] Figure 4 A block diagram of a computer device according to another embodiment of the present application is shown. [Specific implementation method]

[0058] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] Figure 1 A flow chart of a security detection method for issuing online incentive services according to an embodiment of the present application is shown.

[0060] like Figure 1 As shown, according to an embodiment of the present application, a security detection method for issuing online incentive services includes:

[0061] Step 102, determining a second participating user who meets a first preset security rule from among the first participating users obtained in the registration phase of the online incentive service.

[0062] The online incentive service is a service content related to personal protection services or property protection services for the target customer groups of personal protection services or property protection services. For example, for a specified type of life insurance, the content of the online incentive service can be set as follows: if the policy is renewed for one year, the policyholder can participate in the lottery for the first category of prizes, and if the policy is renewed for three years, the policyholder can participate in the lottery for the second category of prizes, and the number of users can be limited for the registration stage and the lottery stage respectively.

[0063] Among them, the first preset security rule is used to reflect the minimum participation conditions that the identity of the participating users in the registration process of the online incentive service must meet.

[0064] In one possible design, it can be detected whether the first participating user obtained during the registration process of the online incentive service is in a list of abnormal users, wherein if the first participating user is not in the list of abnormal users, it is determined that the first participating user is the second participating user.

[0065] That is to say, for users with abnormal traffic who have been identified in the APP and / or mini-program where the online incentive service is located and in any activities related to the online incentive service, they can be added to the blacklist. So far, each time the online incentive service is drawn, it is checked whether the registered participating user is on the blacklist. If the detection result shows that the registered participating user is on the blacklist, the registered participating user is prohibited from participating in further drawing links. As a result, abnormal traffic users can be eliminated before the drawing link, which improves the security of the drawing link.

[0066] Of course, if the detection result shows that the registered user is not on the blacklist, the registered user will be allowed to participate in further drawing steps.

[0067] Step 104: start the extraction phase of the online incentive service for the second participating user.

[0068] After removing the abnormal traffic users from the blacklist, the remaining second participating users will enter the online incentive service extraction stage.

[0069] Step 106, in the extraction phase, randomly select a specified number of third participating users from the second participating users as recipients of the online incentive service, and enter a risk assessment phase.

[0070] In the extraction phase, a random number extraction function can be used to randomly select a specified number of third participating users from all second participating users. The specified number is the number of online incentive services that can be issued.

[0071] Step 108, in the risk assessment phase, based on the individual characteristic information of the third participating user and the activity configuration information of the online incentive service, determine the input information of the preset user risk assessment model.

[0072] Step 110: Based on the input information, the preset user risk assessment model outputs the risk level of the third participating user.

[0073] The individual characteristic information of the third participating user includes but is not limited to the number of times the third participating user participated in the distribution activities of the online incentive service, the number of times he was selected as the transferee in the distribution activities he participated in and the proportion of such number, the number of times he participated in other users' activities, the number of successful assistance, the proportion of successful assistance, the active time period and the number of active times in the APP or mini program where the online incentive service activities are located, etc. It can be said that the individual characteristic information of the third participating user reflects his own historical performance when participating in the distribution activities of the online incentive service, and such historical performance reflects the abnormality of the user to a certain extent.

[0074] The activity configuration information of the online incentive service includes but is not limited to the upper limit of the number of activity participants, the upper limit of the number of activity draws, the content of the activity distribution, the distribution time and validity period of the distribution content, and any other information related to the distribution and redemption of the online incentive service, which reflects the actual situation of the distribution activities of the online incentive service. This actual situation can reflect the safety level of the distribution activities of the online incentive service and the level of attractiveness to abnormal traffic users.

[0075] It can be seen from this that the individual characteristic information of the third participating user and the activity configuration information of the online incentive service both reflect to a certain extent the possibility that the third participating user is an abnormal traffic user, and the risk level indicates the possibility that the third participating user is not a legal transferee. Therefore, the individual characteristic information of the third participating user and the activity configuration information of the online incentive service are correlated with the risk level of the third participating user.

[0076] On this basis, the individual characteristic information of the third participating user in the historical online incentive service distribution activities and the activity configuration information of the online incentive service, as well as the classification of the third participating user (i.e., whether the third participating user is identified as an abnormal traffic user and excluded), can be obtained as a training set to train the preset user risk assessment model. It can be said that the preset user risk assessment model is used to reflect the correlation between the input information and the risk level of the third participating user.

[0077] Step 112: if the risk level is within a preset security risk range, retain the third participating user in the set of transferees of the online incentive service; otherwise, delete the third participating user from the set of transferees of the online incentive service.

[0078] The preset security risk range refers to the range of risk level of the third participating user when he is not an abnormal traffic user. Therefore, if the risk level is within the preset security risk range, it can be determined that the third participating user is not an abnormal traffic user. At this time, the third participating user can be retained in the set of recipients of the online incentive service and the online incentive service can be issued to him.

[0079] On the contrary, if the risk level is not within the preset security risk range, it can be determined that the third participating user has the possibility of being an abnormal traffic user. At this time, in order to ensure the safe distribution of the online incentive service, the third participating user can be deleted from the set of recipients of the online incentive service.

[0080] The above technical solution, in order to solve the technical problem of insufficient accuracy in identifying abnormal users in the process of issuing online incentive services in related technologies, can first conduct a preliminary blacklist check on the participating users before the online incentive service extraction stage, and then after the extraction stage, the risk level of the extracted participating users is assessed by a pre-trained preset user risk assessment model, and the online incentive service is only issued to them when their risk level is within a safe range. Therefore, when conducting online incentive service extraction activities for the target customer groups of personal protection services or property protection services, the security detection capabilities of the users participating in the activities can be strengthened, and users who may have abnormal traffic can be automatically and timely eliminated, so as to avoid the online incentive services being obtained by abnormal traffic users and squeezing the legitimate profit space of the customer groups expected by personal protection services or property protection services, and can improve the user experience of the online incentive service extraction activities and make a positive contribution to the promotion of personal protection services or property protection services.

[0081] In a possible design, a pre-test can be added before the registration phase of the online incentive service is started.

[0082] Specifically, the activity configuration information of the online incentive service may be obtained, wherein the activity configuration information includes but is not limited to an activity review identifier, an activity flow, the distribution content of the online incentive service, the distribution time, and the effective time of the distribution content.

[0083] It can be said that the second preset security rule is used to limit the possible performance of each activity configuration information of the online incentive service when the activity itself is carried out safely.

[0084] On this basis, if the activity configuration information satisfies the second preset security rule, it means that the current drawing activity of the online incentive service is safe and effective, and the registration phase of the online incentive service can be started.

[0085] On the contrary, if any item in the activity configuration information does not satisfy the second preset security rule, it means that the current extraction activity of the online incentive service has security risks.

[0086] At this time, a prompt message may be issued to allow the activity manager to modify the activity configuration information, or the activity configuration information that does not meet the second preset security rule may be automatically modified to be within the requirement range corresponding to the second preset security rule.

[0087] Therefore, the activity itself can be standardized before the extraction activity of the online incentive service begins, which helps to improve the rationality of the activity configuration information of the online incentive service and provide a more reliable basis for determining the input information of the subsequent preset user risk assessment model, thereby improving the accuracy of the assessment results of the preset user risk assessment model.

[0088] In one possible design, step 108 includes: determining the activity type of the online incentive service, and selecting information associated with the activity type from the individual characteristic information of the third participating user and the activity configuration information of the online incentive service as input information of the preset user risk assessment model.

[0089] Previously, it was necessary to first set the associated individual feature information and activity configuration information for each activity type.

[0090] That is to say, for a single activity type, its associated individual feature information and activity configuration information have a higher degree of influence on the user risk assessment results under this activity type than other individual feature information and activity configuration information. In other words, the activity type itself is also one of the factors that affect the security of the extraction activities of online incentive services.

[0091] Therefore, information associated with the activity type can be selected from the individual feature information of the third participating user and the activity configuration information of the online incentive service, that is, some features that play a decisive role in the risk assessment of the participating user can be screened out through the activity type as input information for the preset user risk assessment model. In this way, the input information can be accurately converted to information associated with the activity type and having a greater contribution to the risk assessment results of the participating user, which helps to improve the accuracy of the output results of the preset user risk assessment model, and can more accurately identify whether the participating user is a reasonable transferee, thereby improving the rationality of the issuance of online incentive services.

[0092] In addition, it should be added that after the risk assessment phase of each online incentive service is completed, the activity risk value corresponding to the activity type can be corrected based on the evaluation results of the risk assessment phase, that is, the activity type is re-evaluated through real-time updated data, which helps to more accurately reflect the risk situation of the activity type and provide the activity initiator with a reasonable choice of activity type.

[0093] Optionally, after obtaining the proportion of third participating users eliminated in the risk assessment link among all third participating users each time, the average of this proportion and the proportion of eliminated participating users in historical risk assessment links is calculated as the activity risk value corresponding to the activity type.

[0094] Figure 2A flow chart of a security detection method for issuing online incentive services according to another embodiment of the present application is shown.

[0095] like Figure 2 As shown, according to another embodiment of the present application, a security detection method for issuing online incentive services includes:

[0096] First, before the online incentive service drawing activity goes online, the activity distribution system will manually or automatically review the security issues involved in the activity process and prize pool configuration.

[0097] The review content includes but is not limited to activity plans, activity prizes, third-party activities, sales and warranty, infringement, customer complaint plans, approval chains, and whether the activity launch process is complete.

[0098] Second, during the launch of the activity, abnormal traffic during the activity is identified through online real-time risk control policy rules and model monitoring. Specifically, the online real-time risk control policy rules can be selected to remove blacklisted users from the users participating in the activity.

[0099] Third, before awarding prizes for an event, review the list of winners, assess the risk level of the winning users through a preset user risk assessment model, intercept abnormal rewards in a timely manner, and ensure the safety of marketing funds.

[0100] Specifically, the risk level of winning users can be comprehensively assessed through multi-dimensional data such as their portrait data, activity behavior trajectory data, invitation and / or assistance user information, device data, etc., to detect abnormal winning users and intercept prize distribution in a timely manner, thereby maximizing the security of online incentive service distribution.

[0101] Fourth, after the event is over, trace back the event process, develop a machine learning model to retrieve abnormal traffic offline, and deposit risk labels. That is, trace back the event traffic data, use machine learning, graph algorithms, etc. to build an offline analysis model, fully consider the aggregation and correlation of data, and deposit abnormal traffic risk labels to provide guarantees for the next online incentive service extraction activity.

[0102] The above technical solution can not only monitor abnormal activity traffic through risk control strategy rules during the online incentive service extraction process, but also conduct advance review, timely discovery and rectification of possible security vulnerabilities in the activity process before the online incentive service extraction activity goes online. While ensuring that the overall risk of the activity is controllable, it can enhance the enthusiasm of normal users to participate in the activity and user experience. Furthermore, a multi-dimensional security assessment is conducted on the winning users again before the activity awards, fully ensuring the security of the issuance of online incentive services.

[0103] In addition, the embodiment of the present application provides a security detection device for issuing online incentive services, including:

[0104] A first security detection unit is used to determine a second participating user who meets a first preset security rule from among the first participating users obtained in the registration phase of the online incentive service, wherein the online incentive service is a service content related to the personal protection service or the property protection service for a target customer group of the personal protection service or the property protection service;

[0105] An extraction phase starting unit, used to start the extraction phase of the online incentive service for the second participating user;

[0106] a transferee extraction unit, configured to randomly select a specified number of third participating users from the second participating users as transferees of the online incentive service in the extraction phase, and enter a risk assessment phase;

[0107] a second security detection unit, for determining input information of a preset user risk assessment model in the risk assessment link based on the individual feature information of the third participating user and the activity configuration information of the online incentive service, and for causing the preset user risk assessment model to output the risk level of the third participating user based on the input information, wherein the preset user risk assessment model is used to reflect the correlation between the input information and the risk level of the third participating user, and the risk level indicates the possibility that the third participating user is not a legal transferee;

[0108] A first execution unit, configured to retain the third participating user in the set of transferees of the online incentive service if the risk level is within a preset security risk range;

[0109] The second execution unit is configured to delete the third participating user from the set of transferees of the online incentive service if the risk level is not within a preset security risk range.

[0110] In one embodiment of the present application, optionally, the device further includes:

[0111] An activity configuration information acquisition unit, used to acquire the activity configuration information of the online incentive service before the registration phase of the online incentive service is started, wherein the activity configuration information includes an activity review identifier, an activity flow, the distribution content of the online incentive service, the distribution time, and the effective time of the distribution content;

[0112] The third security detection unit is used to start the registration process of the online incentive service if the activity configuration information meets the second preset security rule.

[0113] In one embodiment of the present application, optionally, the first security detection unit is specifically used to: detect whether the first participating user obtained in the registration phase of the online incentive service is in the list of abnormal users, wherein if the first participating user is not in the list of abnormal users, determine that the first participating user is the second participating user.

[0114] In one embodiment of the present application, optionally, the second safety detection unit includes:

[0115] An input information determination unit is used to determine the activity type of the online incentive service, and select information associated with the activity type from the individual feature information of the third participating user and the activity configuration information of the online incentive service as input information of the preset user risk assessment model.

[0116] In one embodiment of the present application, optionally, the device further includes:

[0117] The pre-configuration unit is used to set the associated individual characteristic information and activity configuration information for each activity type before starting the registration phase of the online incentive service.

[0118] In one embodiment of the present application, optionally, the device further includes:

[0119] The activity type risk assessment unit is used to correct the activity risk value corresponding to the activity type based on the assessment result of the risk assessment link after the risk assessment link is completed.

[0120] The device uses any one of the solutions described in the above embodiments, and therefore has all the above technical effects, which will not be repeated here.

[0121] In addition, in one embodiment, the present application provides a computer device, which may be a server, and its internal structure diagram may be as follows: Figure 3 As shown. The computer device includes a processor, a memory, a network interface and a database connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile and / or volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external client via a network connection. When the computer program is executed by the processor, the security detection method for the issuance of online incentive services described in any of the above embodiments can be implemented.

[0122] In one embodiment, the present application further provides a computer device, which may be a client, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external server via a network connection. When the computer program is executed by the processor, the security detection method for the issuance of online incentive services described in any of the above embodiments can be implemented.

[0123] Any of the above-mentioned computer devices in the embodiments of the present application may exist in various forms, including but not limited to:

[0124] (1) Mobile communication devices: These devices are characterized by their mobile communication functions and their main purpose is to provide voice and data communications. These terminals include: smart phones (such as iPhone), multimedia phones, functional phones, and low-end phones.

[0125] (2) Ultra-mobile personal computer devices: These devices fall into the category of personal computers, have computing and processing capabilities, and generally also have mobile Internet access features. These terminals include: PDA, MID and UMPC devices, such as iPad.

[0126] (3) Portable entertainment devices: These devices can display and play multimedia content. They include audio and video players (such as iPods), handheld game consoles, e-books, as well as smart toys, wearable devices, and portable car navigation devices.

[0127] (4) Server: A device that provides computing services. The server consists of a processor, hard disk, memory, system bus, etc. The server is similar to a general computer architecture, but because it needs to provide highly reliable services, it has higher requirements in terms of processing power, stability, reliability, security, scalability, and manageability.

[0128] (5) Other electronic devices with data interaction functions.

[0129] In addition, an embodiment of the present application provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are used to perform the following steps:

[0130] Determine a second participating user who meets the first preset safety rule from among the first participating users obtained in the registration phase of the online incentive service, wherein the online incentive service is a service content related to the personal protection service or the property protection service for a target customer group of the personal protection service or the property protection service;

[0131] Initiating a drawing phase of the online incentive service for the second participating user;

[0132] In the extraction phase, a specified number of third participating users are randomly selected from the second participating users as recipients of the online incentive service, and enter a risk assessment phase;

[0133] In the risk assessment phase, based on the individual characteristic information of the third participating user and the activity configuration information of the online incentive service, the input information of the preset user risk assessment model is determined;

[0134] Based on the input information, the preset user risk assessment model outputs the risk level of the third participating user, wherein the preset user risk assessment model is used to reflect the correlation between the input information and the risk level of the third participating user, and the risk level indicates the possibility that the third participating user is not a legal transferee;

[0135] If the risk level is within a preset security risk range, the third participating user is retained in the set of transferees of the online incentive service; otherwise, the third participating user is deleted from the set of transferees of the online incentive service.

[0136] It should be noted that the above functions or steps that can be implemented by the computer-readable storage medium or computer device can refer to the relevant description in the aforementioned method embodiment. In order to avoid repetition, they will not be described one by one here.

[0137] The technical solution of the present application is described in detail above in conjunction with the accompanying drawings. The technical solution of the present application can first conduct a preliminary blacklist check on the participating users before the extraction of online incentive services, and then after the extraction, the risk level of the extracted participating users is assessed by a pre-trained preset user risk assessment model, and online incentive services are only issued to them when their risk level is within a safe range. Therefore, when extracting online incentive services for target customer groups of personal protection services or property protection services, the security detection capabilities of participating users can be strengthened, and users who may have abnormal traffic can be automatically and timely eliminated to avoid online incentive services being obtained by abnormal traffic users and squeezing the legitimate profit space of customer groups expected by personal protection services or property protection services. The user experience of online incentive service extraction activities can be improved, and a positive contribution can be made to the promotion of personal protection services or property protection services.

[0138] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0139] It should be understood that although the terms first, second, etc. may be used to describe participating users in the embodiments of the present application, these participating users should not be limited to these terms. These terms are only used to distinguish participating users from each other. For example, without departing from the scope of the embodiments of the present application, the first participating user may also be referred to as the second participating user, and similarly, the second participating user may also be referred to as the first participating user.

[0140] The word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0141] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0142] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0143] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0144] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0145] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A security detection method for online incentive service issuance, characterized in that: include: Determine a second participating user who meets the first preset safety rule from among the first participating users obtained in the registration phase of the online incentive service, wherein the online incentive service is a service content related to the personal protection service or the property protection service for a target customer group of the personal protection service or the property protection service; Initiating a drawing phase of the online incentive service for the second participating user; In the extraction phase, a specified number of third participating users are randomly selected from the second participating users as recipients of the online incentive service, and enter a risk assessment phase; In the risk assessment phase, based on the individual characteristic information of the third participating user and the activity configuration information of the online incentive service, the input information of the preset user risk assessment model is determined; Based on the input information, the preset user risk assessment model outputs the risk level of the third participating user, wherein the preset user risk assessment model is used to reflect the correlation between the input information and the risk level of the third participating user, and the risk level indicates the possibility that the third participating user is not a legal transferee; If the risk level is within a preset security risk range, the third participating user is retained in the set of transferees of the online incentive service; otherwise, the third participating user is deleted from the set of transferees of the online incentive service.

2. The method according to claim 1, characterized in that: Before the registration phase of the online incentive service is initiated, it also includes: Acquire activity configuration information of the online incentive service, wherein the activity configuration information includes an activity review identifier, an activity flow, the distribution content of the online incentive service, the distribution time, and the effective time of the distribution content; If the activity configuration information satisfies the second preset security rule, the registration phase of the online incentive service is initiated.

3. The method according to claim 1, characterized in that Determining a second participating user who meets a first preset safety rule from among the first participating users obtained in the registration phase of the online incentive service includes: Detecting whether the first participating user obtained during the registration phase of the online incentive service is in a list of abnormal users; If the first participating user is not in the abnormal user list, the first participating user is determined to be the second participating user.

4. The method according to any one of claims 1 to 3, characterized in that The step of determining input information of a preset user risk assessment model based on the individual feature information of the third participating user and the activity configuration information of the online incentive service includes: Determining the activity type of the online incentive service; Information associated with the activity type is selected from the individual feature information of the third participating user and the activity configuration information of the online incentive service as input information of the preset user risk assessment model.

5. The method according to claim 4, characterized in that Before starting the registration phase for the online incentive service, it also includes: Associated individual characteristic information and activity configuration information are set for each activity type.

6. The method according to claim 4, characterized in that After the risk assessment phase is completed, it also includes: Based on the assessment result of the risk assessment link, the activity risk value corresponding to the activity type is corrected.

7. A security detection device for online incentive service issuance, characterized in that: include: A first security detection unit is used to determine a second participating user who meets a first preset security rule from among the first participating users obtained in the registration phase of the online incentive service, wherein the online incentive service is a service content related to the personal protection service or the property protection service for a target customer group of the personal protection service or the property protection service; An extraction phase starting unit, used to start the extraction phase of the online incentive service for the second participating user; a transferee extraction unit, configured to randomly select a specified number of third participating users from the second participating users as transferees of the online incentive service in the extraction phase, and enter a risk assessment phase; a second security detection unit, for determining input information of a preset user risk assessment model in the risk assessment link based on the individual feature information of the third participating user and the activity configuration information of the online incentive service, and for causing the preset user risk assessment model to output the risk level of the third participating user based on the input information, wherein the preset user risk assessment model is used to reflect the correlation between the input information and the risk level of the third participating user, and the risk level indicates the possibility that the third participating user is not a legal transferee; A first execution unit, configured to retain the third participating user in the set of transferees of the online incentive service if the risk level is within a preset security risk range; The second execution unit is configured to delete the third participating user from the set of transferees of the online incentive service if the risk level is not within a preset security risk range.

8. The device according to claim 1, characterized in that Also includes: An activity configuration information acquisition unit, used to acquire the activity configuration information of the online incentive service before the registration phase of the online incentive service is started, wherein the activity configuration information includes an activity review identifier, an activity flow, the distribution content of the online incentive service, the distribution time, and the effective time of the distribution content; The third security detection unit is used to start the registration process of the online incentive service if the activity configuration information meets the second preset security rule.

9. A computer device, characterized in that: include: at least one processor; and, a memory communicatively coupled to the at least one processor; The memory stores instructions executable by the at least one processor, and the instructions are configured to enable the processor to execute the method according to any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that: Computer executable instructions are stored, and the computer executable instructions are configured to execute the method according to any one of claims 1 to 6.

Images