User Identification Using Real Environmental Human Computer Interaction Behavior

Abstract

In this paper, a new user identification method is presented using real environmental human-computer-interaction (HCI) behavior data to improve method usability. User behavior data in this paper are collected continuously without setting experimental scenes such as text length, action number, etc. To illustrate the characteristics of real environmental HCI data, probability density distribution and performance of keyboard and mouse data are analyzed through the random sampling method and Support Vector Machine(SVM) algorithm. Based on the analysis of HCI behavior data in a real environment, the Multiple Kernel Learning (MKL) method is first used for user HCI behavior identification due to the heterogeneity of keyboard and mouse data. All possible kernel methods are compared to determine the MKL algorithm's parameters to ensure the robustness of the algorithm. Data analysis results show that keyboard data have a narrower range of probability density distribution than mouse data. Keyboard data have better performance with a 1-min time window, while that of mouse data is achieved with a 10-min time window. Finally, experiments using the MKL algorithm with three global polynomial kernels and ten local Gaussian kernels achieve a user identification accuracy of 83.03% in a real environmental HCI dataset, which demonstrates that the proposed method achieves an encouraging performance.

A Systematic Survey on Examinees Identity Authentication in Online Distant Exams

“…a biometric authentication based on mouse dynamic and Keystroke has been disclosed; They gathered data on mouse movement and keystrokes from 53 people using software; They developed a robust, trusted algorithm to function on a continuous authentication system. Several new mouse movement features; divided mouse events into four categories: single click, double click, move, and dragand-drop; They compared their findings to those of other studies and discovered that their proposed methodology produces better results [160].…”