Risk control method based on gesture monitoring on mobile terminal and related device

Abstract

The invention relates to a risk control method based on gesture monitoring on a mobile terminal and a related device, and belongs to the technical field of risk monitoring, and the method comprises the steps: monitoring and continuously collecting interface operation feature data generated in a man-machine interaction process; obtaining interface operation characteristic data in a preset time period; dividing the interface operation characteristic data into multiple sections of sub-interface operation characteristic data; adding a corresponding terminal service label in a human-computer interaction process to each sub-interface operation characteristic data, and inputting the terminal service label into the risk control model to obtain a sub-gesture label and an abnormal score of each sub-interface operation characteristic data; and calculating a risk control score corresponding to the user according to the sub-gesture label of each sub-interface operation feature data, the abnormal score of the sub-gesture label and the terminal service label corresponding to each sub-interface operation feature data, so as to determine whether there is a risk or not. The reliability of risk control on the mobile terminal is effectively improved. The invention also relates to a blockchain technology. The sub-interface operation feature data is stored in the blockchain.

Description

technical field [0001] The present application relates to the technical field of risk monitoring, in particular, to a risk control method and related devices based on gesture monitoring on a mobile terminal. Background technique [0002] Generally, in risk monitoring at present, there is a method of judging gestures for user monitoring, through images collected by camera equipment, or a method of providing a light-emitting unit, by acquiring the image generated by the light beam reflected by the hand, and through the processing circuit. Obtain the hand image, identify all the hand skeletons on the image, and judge whether the recognized human skeleton information matches the human skeleton information stored in the database, so as to identify the user's identity for risk control. However, these methods inevitably use high-definition devices, which will consume a lot of cost, easily cause unnecessary troubles, and cause poor user experience; moreover, in the mobile terminal s...

AI Technical Summary

Problems solved by technology

However, these methods inevitably use high-definition devices, which will consume a lot of cost, easily cause unnecessary troubles, and cause poor user experience; moreover, in the mobile terminal scenario, these devices do not exist, and users cannot use Behavioral characteristics are used to detect user identity, and the reliability of risk control is low

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