User equipment authentication method, device and equipment based on APP installation list grouping

Abstract

The invention relates to a user equipment authentication method based on APP installation list grouping. The method comprises the following steps: acquiring APP installation lists of a plurality of pieces of historical user equipment, wherein the APP installation lists comprise APP information installed on the plurality of pieces of historical user equipment; determining a feature matrix of the historical user equipment according to the APP information installed on the multiple pieces of historical user equipment; and grouping the plurality of historical user equipment according to the feature matrix of the historical user equipment to obtain group feature information of each historical user equipment, so that the obtained grouping result is more accurate, and it can be guaranteed that the group feature information of the users is almost consistent; and establishing and training a machine learning model based on the group feature information of each historical user equipment and the performance information of each historical user equipment in the Internet service, and authenticating the new user equipment applying for the Internet service by using the machine learning model, so that an authentication result obtained in this way is more accurate.

Description

technical field [0001] The present disclosure relates to the field of computer information processing, in particular, to a user equipment authentication method, device, electronic equipment, and computer-readable medium based on APP installation list grouping. Background technique [0002] With the rapid development of the Internet, more and more users apply for Internet services through user equipment. When a user applies for an Internet service, the identity of the user needs to be authenticated. At present, multiple users are grouped first to obtain multiple user groups. For example, the traditional methods for dividing user groups mainly fall into the following categories: 1. Grouping based on user qualifications, such as having a degree but not a degree, and having a card or no card; 2. Based on the performance period of users on the platform, such as new users, second-new users Group users and old users; 3. Group based on user channels, such as main process users, AP...

AI Technical Summary

Problems solved by technology

Based on the above-mentioned traditional user group division method, the obtained grouping results can only show that the roughly behavioral data of the users in the user group are consistent, but cannot indicate that the behavioral characteristics of the users in the user group are consistent

Therefore, based on the above-mentioned grouping method, the accuracy of the obtained grouping result is low. Furthermore, based on the above-mentioned grouping result, the user who applies for the Internet service is authenticated, and the accuracy of the authentication result is low.

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