Human-computer identification method and device based on sliding trajectory, and electronic equipment

A technology of sliding trajectory and man-machine recognition, which is applied in the computer field, can solve the problems of low accuracy rate and achieve the effect of improving accuracy rate, good recognition effect and improving robustness

Active Publication Date: 2018-02-09
北京钱袋宝支付技术有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The embodiment of the present application provides a human-machine recognition method based on the sliding trajectory, which solves the problem of

Method used

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  • Human-computer identification method and device based on sliding trajectory, and electronic equipment
  • Human-computer identification method and device based on sliding trajectory, and electronic equipment
  • Human-computer identification method and device based on sliding trajectory, and electronic equipment

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0026] A human-machine recognition method based on sliding trajectory disclosed in the present application, such as figure 1 As shown, the method includes: step 100 to step 120.

[0027] Step 100, determine the preset dimension feature code of the historical sliding track that has passed the verification, and the feature code of the historical sliding track is based on the reference distribution feature of at least one time window.

[0028] During specific implementation, the sliding track data of the verified user in the past period of time is collected, and feature encoding is performed on each sliding track based on the preset dimension to obtain the feature encoding of the preset dimension. During specific implementation, the preset dimension feature encoding includes, but is not limited to: any or all of angle encoding and speed encoding.

[0029] Then, based on at least one time window, the reference distribution characteristics of each preset dimensional feature code a...

Embodiment 2

[0040] Such as figure 2 As shown, based on the first embodiment, the human-machine recognition method based on the sliding trajectory disclosed in another specific embodiment of the present application includes: step 200 to step 220 .

[0041] Step 200, determine the angle code of the historical sliding track that has passed the verification, and the angle code of the real-time sliding track is based on the reference distribution characteristics of at least one time window.

[0042] During specific implementation, determining the preset dimension feature encoding of the historical sliding track passed through verification, and the feature encoding of the historical sliding track based on the reference distribution feature of at least one time window, includes: for different dimensions, perform the following operations respectively: according to the user The historical sliding track data, determine the feature encoding of the preset dimension of each historical sliding track a...

Embodiment 3

[0111] Such as Figure 4 As shown, based on Embodiment 1 and Embodiment 2, another specific embodiment of the present application discloses a human-machine recognition method based on a sliding track, including: Step 400 to Step 420 .

[0112] Step 400, determine the velocity code of the historical sliding trajectory that has passed the verification, and the velocity encoding of the real-time sliding trajectory is based on the reference distribution characteristics of at least one time window.

[0113]Taking the preset dimension feature encoding as including speed encoding, and the at least one time window being a 5-minute time window and a 1-hour time window as an example, it is determined that the preset dimension feature encoding of the verified historical sliding track is based on at least one time window When referring to the distribution characteristics of the window: first, according to the user's historical sliding track data, determine the speed code of each historica...

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Abstract

The invention provides a human-computer identification method based on a sliding trajectory, belongs to the technical field of computers and is used for solving the problem of low accuracy when a human-computer identification method simulates a sliding trajectory input by a user in the prior art. The method comprises the following steps that: determining the preset dimension feature coding of a historical sliding trajectory which is qualified, and the reference distribution feature of the feature coding of a historical sliding trajectory on the basis of at least one time window; determining the preset dimension feature coding of a real-time sliding trajectory to be verified, and the distribution feature to be verification of the feature coding of a historical sliding trajectory on the basis of at least one time window; and if the distribution feature to be verification on the basis of a certain time window is not matched with the reference distribution feature, determining that the real-time sliding trajectory to be verified is a machine simulation sliding trajectory. By use of the method disclosed by the embodiment of the invention, accuracy for identifying the machine simulationsliding trajectory can be effectively improved.

Description

technical field [0001] The present application relates to the field of computer technology, in particular to a method and device for man-machine identification based on sliding tracks, and electronic equipment. Background technique [0002] When logging in to a mobile terminal or an application or a website on a mobile terminal, it is usually necessary to authenticate the real identity of the user, and it is already a very common user identification method to identify the real identity of the user based on the sliding track. To some extent, authentication through sliding traces can increase the difficulty of malicious attacks on login / registration interfaces, but it can still be cracked by simulating user sliding traces by machines. In the prior art, when identifying real-person operations or machine-simulated user operations based on sliding tracks, it mainly monitors and detects source IPs with abnormal login / registration behaviors (for example, frequent sliding track veri...

Claims

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Application Information

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IPC IPC(8): G06F21/31G06K9/48
CPCG06F21/31G06V10/469
Inventor 张振华张宇仁高洋波刁士涵赵翔宇李孟瑶
Owner 北京钱袋宝支付技术有限公司
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