CN115994791A - Risk judgment method based on integral user state snapshot and quantitative analysis - Google Patents
Risk judgment method based on integral user state snapshot and quantitative analysis Download PDFInfo
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Abstract
And setting a risk identification rule model according to the integral service characteristics, and configuring different quantized scores. And in each characteristic link of the user using the point system, snapshot recording and summarizing the user state, wherein the snapshot recording and summarizing comprises the current time, the current business, the service ID, the equipment ID, the mobile phone number, the point value, the order value and the like. And taking the user ID as an index, quantitatively calculating the risk value of each user in real time according to a risk identification rule model, and carrying out system prompt and early warning on the user entering the risk area according to the set threshold value. The method and the system of the invention comprise the following steps: the system comprises an integral user state snapshot information collection module, an integral risk rule module, a quantitative analysis and risk judgment module and a risk judgment result set module.
Description
Technical Field
The invention relates to the technical field of integral application, in particular to a risk judging method based on integral user state snapshot and quantitative analysis.
Background
Most of the point service systems are related to user personal information, user point data, point exchange information, payment information and the like, and have higher information security requirements. In the actual integration business operation process, most risks come from access and attack of fake users and the like. Therefore, in the point service system, the risk of the user is identified, and the point service system is one of core capabilities for preventing the risk of the point service process. At present, most integration service systems generally adopt a plurality of authentication modes of single-node users or user tracing and preventing after abnormal access/attack and the like in the aspect of identifying users. But the malicious access or attack of the fake user is easy to avoid after the fake user is familiar with the prevention rule. The method is characterized in that the method is combined with the modern Internet and big data technology, various behavior tracks are subjected to condition snapshot and storage in the process of using the integral service by a user, and the user state snapshot data is subjected to backtracking processing and quantitative analysis by utilizing big data in combination with a risk rule model to obtain a user risk index, so that early user risk pre-judgment is provided for an integral system, and better risk control is realized.
Disclosure of Invention
The invention provides a risk judging method based on integral user state snapshot and quantitative analysis. And setting a risk identification rule model according to the integral service characteristics, and configuring different quantized scores. And in each characteristic link of the user using the point system, snapshot recording and summarizing the user state, wherein the snapshot recording and summarizing comprises the current time, the current business, the service ID, the equipment ID, the mobile phone number, the point value, the order value and the like. And taking the user ID as an index, quantitatively calculating the risk value of each user in real time according to a risk identification rule model, and carrying out system prompt and early warning on the user entering the risk area according to the set threshold value. The method and the system of the invention comprise the following steps: the system comprises an integral user state snapshot information collection module, an integral risk rule module, a quantitative analysis and risk judgment module and a risk judgment result set module.
1. Integrating user state snapshot information collection module: in the integral service system, condition snapshot and information storage are carried out aiming at links of using multiple service types by users. The status information includes current time, current business, service ID, device ID, cell phone number, credit value, order value, etc.
2. An integral risk rule model module: and setting a plurality of integration rule models according to the integration service characteristics and combining risk control experience, and configuring corresponding scores. If the same equipment logs in N accounts within a certain time period, 30 minutes are obtained; the same equipment does not change in position and switches a plurality of IPs, and 50 points are obtained; the order behaviors of the household articles are N or more in M months, and 20 points are obtained; the higher the score, the higher the risk.
3. And the quantitative analysis and risk judgment module is used for: and carrying out integral risk rule analysis processing on the user state snapshot data by utilizing a big data technology to obtain a risk index aiming at the current user, and outputting risk judgment result information to a risk judgment result module. The module is also responsible for setting rule contents and allocation of the integral risk rule model module.
And a judging result set module: and the receiving quantitative analysis and risk judgment module obtains output information, and stores the judgment result for the integration system to perform safety intervention and other processes.
Drawings
Fig. 1 is a system structure diagram of a risk determination method based on integral user state snapshot and quantitative analysis.
Fig. 2 is a main flow chart of a risk determination method system based on integral user state snapshot and quantitative analysis.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, in an embodiment of the present invention, the method and system of the present invention include: the system comprises an integral user state snapshot information collection module (1), an integral risk rule model module (2), a quantitative analysis and risk judgment module (3) and a risk judgment result set module (4).
1. Integrating user state snapshot information collection module (1): in the integral service system, condition snapshot and information storage are carried out aiming at links of using multiple service types by users. The status information includes current time, current business, service ID, device ID, cell phone number, credit value, order value, etc.
2. Integral risk rule model module (2): and setting a plurality of integration rule models according to the integration service characteristics and combining risk control experience, and configuring corresponding scores. If the same equipment logs in N accounts within a certain time period, 30 minutes are obtained; the same equipment does not change in position and switches a plurality of IPs, and 50 points are obtained; the order behaviors of the household articles are N or more in M months, and 20 points are obtained; the higher the score, the higher the risk.
3. Quantitative analysis and risk judgment module (3): and (4) carrying out integral risk rule analysis processing on the user state snapshot data by utilizing a big data technology to obtain a risk index aiming at the current user, and outputting risk judgment result information to a risk judgment result module (4). The module is also responsible for setting rule contents and distribution obtained by the integral risk rule model module (2).
4. Risk determination result set module (4): and the receiving quantitative analysis and risk judgment module obtains output information, and stores the judgment result for the integration system to perform safety intervention and other processes.
The main flow of the system is shown in figure 2.
Claims (5)
1. A risk judging method based on integral user state snapshot and quantitative analysis is characterized by comprising the following steps of: setting a risk identification rule model according to the integral service characteristics, and configuring different quantized scores; the user uses each characteristic link of the point system to record and summarize the user state, including the current time, the current business, the service ID, the equipment ID, the mobile phone number, the point value, the order value and the like; the user ID is used as an index, the risk value of each user is calculated in real time in a quantitative mode according to a risk identification rule model, and system prompt and early warning are carried out on users entering a risk area according to a set threshold value; the method and the system of the invention comprise the following steps: the system comprises an integral user state snapshot information collection module, an integral risk rule module, a quantitative analysis and risk judgment module and a risk judgment result set module.
2. The risk determination method based on integral user state snapshot and quantitative analysis of claim 1, wherein: integrating user state snapshot information collection module: in the integral service system, condition snapshot and information storage are carried out aiming at links of using multiple service types by users; the status information includes current time, current business, service ID, device ID, cell phone number, credit value, order value, etc.
3. The risk determination method based on integral user state snapshot and quantitative analysis of claim 1, wherein: an integral risk rule model module: according to the integral service characteristics, combining risk control experience, setting a plurality of integral rule models, and configuring corresponding scores; the higher the value, the higher the risk.
4. The risk determination method based on integral user state snapshot and quantitative analysis of claim 1, wherein: and the quantitative analysis and risk judgment module is used for: carrying out integral risk rule analysis processing on the user state snapshot data by utilizing a big data technology to obtain a risk index aiming at the current user, and outputting risk judgment result information to a risk judgment result module; and the rule content and the allocation of the score risk rule model module are set.
5. The risk determination method based on integral user state snapshot and quantitative analysis of claim 1, wherein: risk determination result set module: and the receiving quantitative analysis and risk judgment module obtains output information, and stores the judgment result for the integration system to perform safety intervention and other processes.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116957666A (en) * | 2023-09-19 | 2023-10-27 | 南京大数据集团有限公司 | Integral data processing method and system based on circulation feature recognition |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116957666A (en) * | 2023-09-19 | 2023-10-27 | 南京大数据集团有限公司 | Integral data processing method and system based on circulation feature recognition |
| CN116957666B (en) * | 2023-09-19 | 2024-04-02 | 南京大数据集团有限公司 | Integral data processing method and system based on circulation feature recognition |
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