In this research, we propose a novel biometric system for static user authentication that homogeneously combines mouse dynamics, visual search capability and short-term memory effect. The proposed system introduces the visual search capability, and short-term memory effect to the biometric-based security world for the first time. The use of a computer mouse for its dynamics, and as an input sensor for the other two biometrics, means no additional hardware is required than the standard mouse. Experimental evaluation showed the system effectiveness using variable or one-time passwords. All of these attributes qualify the proposed system to be effectively deployed as a static authentication mechanism.Extensive experimentation was done using 2740 sessions collected from 274 users. To measure the performance, a computational statistics model was specially designed and used; a statistical classifier based on Weighted-Sum produced an Equal Error Rate (EER) of 2.11%.
Modeling and quantifying different human factors continue to be one of the major challenges in introducing new biometric systems. For example, drivers of some of our behavior differences are still mysteries, and hence cannot be modeled. In this paper, we propose a novel biometric system; it introduces the visual search and short-term memory human factors to the world of biometrics. This homogeneous system uses only the standard mouse as an input sensor for the two biometric factors. Experimental evaluation was performed using mass enrollment of 275 participants, and Neural Network for classification. Results showed an Equal Error Rate ( EER) of 3.88%.
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