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A method and device for man-machine recognition based on sliding trajectory, electronic equipment

A sliding trajectory, human-machine recognition technology, applied in the computer field, can solve problems such as low accuracy, and achieve the effect of improving accuracy, good recognition effect, and improving robustness

Active Publication Date: 2019-03-15
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 low accuracy when the human-computer recognition method in the prior art recognizes that the machine simulates the user inputting the sliding trajectory

Method used

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  • A method and device for man-machine recognition based on sliding trajectory, electronic equipment
  • A method and device for man-machine recognition based on sliding trajectory, electronic equipment
  • A method and device for man-machine recognition based on sliding trajectory, electronic equipment

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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 present application provides a human-machine recognition method based on a sliding trajectory, which belongs to the field of computer technology, and is used to solve the problem of low accuracy when the human-computer recognition method in the prior art identifies a machine to simulate a user inputting a sliding trajectory. The method includes: determining the preset dimension feature code of the verified historical sliding track, and the feature coding of the historical sliding track is based on the reference distribution characteristics of at least one time window; determining the preset dimension of the real-time sliding track to be verified Feature coding, and the feature coding of the real-time sliding trajectory is based on the distribution feature to be verified in the at least one time window; if the distribution feature to be verified based on a certain time window does not match the reference distribution feature, then The real-time sliding track to be verified is determined as a machine simulated sliding track. The method disclosed in the embodiment of the present application can effectively improve the accuracy of identifying the simulated sliding track of a machine.

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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Patent Type & Authority Patents(China)
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