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Track-based man-machine recognition method for sliding verification codes

An identification method and code man-machine technology, applied in the field of trajectory-based sliding verification code man-machine identification, can solve problems such as the hysteresis of confrontation methods, achieve the effect of good confrontation protection and improve the accuracy rate

Active Publication Date: 2018-07-17
CHECC DATA CO LTD +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The existing detection technology is mainly for machine identification, and the way of fighting against the constantly updated machine behavior has a lag, and the detection update is often after certain losses are caused by black production tools

Method used

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  • Track-based man-machine recognition method for sliding verification codes
  • Track-based man-machine recognition method for sliding verification codes
  • Track-based man-machine recognition method for sliding verification codes

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0037] A trajectory-based human-machine recognition method for sliding verification codes, comprising the following steps:

[0038] S1: collect user trajectory data;

[0039] Collect user trajectory data (x, y, t), including the horizontal coordinate x and vertical coordinate y at different time points t during the trajectory triggering process. Specifically, it is to obtain the trajectory record of the user during the sliding verification code trigger process, Provide data support for the construction of the multi-dimensional feature system of the sliding verification code code.

[0040] S2: Construct a multi-dimensional feature system based on trajectory data;

[0041] Based on the discovery of two modes, one is the end-retracement phenomenon of human trajectories; the other is the phenomenon of human trajectories being far, fast, and near-slow; multi-dimensional feature extraction is carried out, and then a multi-dimensional feature system is constructed to facilitate the ...

Embodiment 2

[0046] On the basis of Example 1, the multi-dimensional feature system includes X features, Y features, and T features.

[0047] The present invention mainly uses the horizontal feature x to describe the behavior habits of "people" when performing sliding verification, and uses the vertical feature y to describe the characteristics of "machines", and uses the time feature T as a supplement to describe the difference between "human" and "machine". like figure 2 shown.

[0048] Further, the specific steps of the X feature extraction are as follows:

[0049] S201: Extracting the X feature class, and normalizing the horizontal coordinate x of the trajectory;

[0050] S202: Combining the phenomenon of "far, fast, near slow" in human trajectory mode 2, the trajectory will be divided into the first half and the second half;

[0051] Specifically, "far, fast, near, slow" indicates that in the process of sliding the verification code, the speed is faster when the target point is fa...

Embodiment 3

[0075] On the basis of embodiment 1, the specific steps of the design of the human-machine recognition model of the step S3 are as follows:

[0076] S301: Input the features in the multi-dimensional feature system into multiple training models for algorithm training;

[0077] S302: Perform linear weighting on the training output of the feature algorithm;

[0078] Further, the training model includes: CatBoost model, XGBoost model, RandomForest model, LogisticRegression model.

[0079] like image 3 As shown, specifically, the probability values ​​of the training outputs of the CatBoost model, XGBoost model, RandomForest model, and LogisticRegression model are linearly weighted to obtain a human-machine recognition model linearly weighted by the four basic models.

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Abstract

The invention discloses a track-based man-machine recognition method for sliding verification codes. The method comprises the following steps of: acquiring track data of a user; constructing a multi-dimensional feature system according to the track data; and carrying out track differentiation on the multi-dimensional feature system according to a designed man-machine recognition model. According to the method, the multi-dimensional feature system is designed by combining two phenomena of human tracks, and features are used for describing sliding verification code habits of users, so that useroperations and machine simulations are differentiated, advantages are provided in confront with black product tools of attackers, and a relatively good confront protection effect is provided.

Description

technical field [0001] The invention relates to the technical field of biometric authentication, in particular to a trajectory-based human-machine identification method for sliding verification codes. Background technique [0002] As a biometric authentication technology, the sliding verification code can meet the security requirements of the current network environment for identity authentication. It has been widely used in a variety of man-machine verification products. This verification method is not only easy for users to understand and remember, but also greatly increases the violence. Crack difficulty. At the same time, it has also attracted the attention of attackers. Attackers have developed black production tools that can imitate human behavior and began to challenge the mouse trajectory during the verification process of sliding verification codes. [0003] The attackers generate human-like trajectory batch operations through black production tools to bypass detec...

Claims

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Application Information

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IPC IPC(8): G06F21/36G06K9/62
CPCG06F21/36G06F18/24G06F18/214
Inventor 张敏陈媛阳小龙朱翔宇孙奇福
Owner CHECC DATA CO LTD
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