期刊论文

Research of Human Machine Identification for Sliding Verification Code Based on Neural Network

中文

Shuxue Lilun yu Yingyong

1006-8074

2017

37

3

43-50

湖南省教育厅重点课题(17A003)资助.

本校为第一机构

在滑动式验证码完成滑动验证的过程中,正确区分出操作者是“机器”还是“个人”对于网络安全至关重要.本文利用人和机器完成验证所留下的滑动轨迹提取特征,运用机器学习中的神经网络算法和MATLAB软件对其进行实证研究和分析,建立神经网络分类模型预测验证操作者的类别.结果表明,BP神经网络模型预测准确度很高,在一定程度上为网络安全提供了保障.

In the process of sliding verification,it is very important to distinguish whether the drill author is "machine"or "personal".In this paper,we use the neural network algorithm and MATLAB software to make an empirical study and analysis on the characteristics of the sliding trajectory extraction left by human and machine,and establish the classification model of the neural network to predict the operator.The results show that the BP neural network model has high prediction accuracy a...