Dr. Lixin Yu Profile

Dr. Lixin Yu

at Alcorn State Univ.

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Proceedings Article | 27 May 2022 Presentation + Paper

Improving cybersecurity through deep learning on keystroke and mouse dynamics

Yufeng Zheng, Lixin Yu, Sardar Haque, Ping Zhang, Adel Elmaghraby

Proceedings Volume 12100, 1210005 (2022) https://doi.org/10.1117/12.2620104

KEYWORDS: Biometrics, Behavioral biometrics, Distance measurement, Neural networks, Data modeling, Mahalanobis distance

Read Abstract +

Username, password, and biometrics are three-factor authentication for cybersecurity enhancement. Adding keystroke and mouse biometrics to authentication will definitely improves the cybersecurity. Keystroke dynamics refers to the process of measuring and assessing human’s typing rhythm on digital devices. Keystroke timing information such as digraph, dwell time and flight time are used in our experimental datasets. Mouse dynamics records mouse motion (speed), left-, right-, or double-clicking timing information. Our own dataset includes both types of dynamics from same group of subjects. We develop recurrent neural network (RNN) models and support vector machine (SVM) models to represent user’s biometrics. Keystroke and mouse dynamics can be used as features fed to the models separately for user verification or identification. Feature fusion is applied to improve the accuracy. Our results show the RNN method is better than traditional methods like SVM, and fusion can further improve the performance.

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