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Frontiers of Information Technology & Electronic Engineering >> 2019, Volume 20, Issue 7 doi: 10.1631/FITEE.1700442

Man-machine verification of mouse trajectory based on the random forestmodel

1. Department of Automation, School of Information Science and Technology, University of Science and Technology of China, Hefei 230022, China
2. State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei 230027, China

Available online: 2019-08-30

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Abstract

Identifying code has been widely used in man-machine verification to maintain network security. The challenge in engaging man-machine verification involves the correct classification of man and machine tracks. In this study, we propose a random forest (RF) model for man-machine verification based on the mouse movement trajectory dataset. We also compare the RF model with the baseline models (logistic regression and support vector machine) based on performance metrics such as precision, recall, false positive rates, false negative rates, F-measure, and weighted accuracy. The performance metrics of the RF model exceed those of the baseline models.

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