Behavior data processing method and device, apparatus and readable storage medium

Abstract

The invention provides a behavior data processing method and device, an apparatus and a readable storage medium. The method comprises the steps of obtaining the current behavior data of a user; extracting the first behavior features of the current behavior data from the current behavior data; obtaining the second behavior features of the current behavior data according to the first behavior features of the current behavior data; obtaining a behavior vector of the current behavior data according to the first behavior features of the current behavior data and the second behavior features of thecurrent behavior data; and comparing the behavior vector of the current behavior data with a standard behavior vector to verify the user. According to the method, by extracting the features of the behavior data, the behavior data can be efficiently utilized for identity recognition.

Description

technical field [0001] The present disclosure relates to the technical field of identity authentication, in particular, to a behavior data processing method, device, equipment and readable storage medium. Background technique [0002] In an environment where mobile communication devices are widely popularized, convenient mobile devices also bring problems of information security and payment security to users. Payment through mobile devices is one of people's daily application needs, and it is also an application scenario with the most security issues. The security of mobile payment is mainly realized through identity authentication technology. Some related technologies use password-based identity authentication technology, but there are risks such as password leakage, brute force cracking, and coercion cracking; other related technologies use identity authentication technology based on dynamic passwords (One-time Password, abbreviated as OTP). Risks such as man-in-the-midd...

AI Technical Summary

Problems solved by technology

The behavior data collected in some identity authentication technologies based on user behavior is rich in content, and a large number of features are extracted from the collected data, resulting in a huge amount of authentication calculations, which affects the efficiency and performance of identification; the collected behavior data is of a single type, and the judgment reference index Insufficient comprehensiveness leads to low identification accuracy; no distinction is made between different usage scenarios of users, which also leads to low identification accuracy

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