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Method for detecting man-machine mouse tracks on basis of convolutional neural networks

A convolutional neural network, mouse trajectory technology, applied in computer parts, instruments, characters and pattern recognition, etc., can solve the problems of long update cycle of detection model and insufficient model generalization ability, and achieve good generalization ability and simplification. The effect of the feature extraction process

Inactive Publication Date: 2018-03-06
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

This leads to, on the one hand, the low-level semantic features extracted manually make the generalization ability of the model insufficient, and on the other hand, the update cycle of the detection model is longer

Method used

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  • Method for detecting man-machine mouse tracks on basis of convolutional neural networks
  • Method for detecting man-machine mouse tracks on basis of convolutional neural networks
  • Method for detecting man-machine mouse tracks on basis of convolutional neural networks

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Embodiment Construction

[0040] The present invention will be described in detail below in conjunction with the accompanying drawings.

[0041] The invention discloses a human-machine mouse trajectory detection method based on a convolutional neural network, and the specific implementation steps include:

[0042] (1) Preprocess the mouse trajectory sampling data in the training sample library and the test sample library to obtain the original features with the same length. The flow chart of the extraction of original features is as follows: figure 1 shown.

[0043] (2) Standardize the original features extracted in (1), and then automatically perform feature extraction through the convolutional neural network, and then train and predict. The structure diagram of convolutional neural network is as follows figure 2 shown.

[0044] The preprocessing step in described step (1) is as follows:

[0045] (11) Each mouse track sampling data records the coordinate information of the mouse at different sam...

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Abstract

The invention belongs to the field of machine learning and pattern recognition, and particularly discloses a method for detecting man-machine mouse tracks on the basis of convolutional neural networks. The method includes preprocessing mouse track sampled data to obtain original characteristics such as coordinate and time characteristics, differential characteristics, speed characteristics, acceleration characteristics and direction characteristics with consistent lengths; carrying out standardized processing on the original characteristics, automatically extracting advanced semantic characteristics by the aid of the convolutional neural networks and carrying out training and prediction. The method has the advantages that characteristic extraction procedures can be simplified, the convolutional neural networks are excellent in generalization capacity, and machine attack means in man-machine verification products can be discriminated.

Description

technical field [0001] The invention belongs to the field of machine learning and pattern recognition, relates to deep learning and network security related technologies, and is specifically a convolutional neural network-based human-machine mouse trajectory detection method. Background technique [0002] Currently, mouse track detection is widely used in various man-machine verification products, which is not only convenient for users to operate, but also greatly increases the difficulty of brute force cracking. However, attackers can generate human-like trajectories through black production tools, operate in batches to bypass detection, and continuously upgrade their means of falsifying data during the confrontation process to continuously bypass the same upgraded detection technology. We expect to use machine learning algorithms to improve the detection rate of various machine behaviors in human-machine verification, including the detection of new attack methods that appe...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
CPCG06V30/36
Inventor 漆进张通胡顺达
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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