Content area

Abstract

Authentication systems in which eye is used for entering the password are categorized into two gaze-based and gesture-based groups. In the accurate point-of-regard gaze measurements, a key subject with gaze-based authentication schemes is needed. Gesture-based systems are based on identifying the eye movement tracking, hence, there is no need to estimate the precise point of the user’s vision. Although gesture-based systems are superior to gaze-based methods, they are not appropriate and applicable in remembering the equivalent gesture of any suitable number due to the high memory overhead. This paper introduces the new Eye Gesture Blink Password authentication system (EGBP). The system is based on four basic ideas: system design, the algorithm of finding fixations without having to track pupils in all frames, allowing users to blink as part of the password and the new method of finding the user password using the angle formed between the fixations. EGBP has several basic advantages compared to existing authentication systems including the no need for a commercial eye tracker that lowers the system’s cost, removing the calibration step that increases the speed and requires less processing, and choosing a maximum length code that reduces the likelihood of the likeness of the selected password and increases security. The possibility of simply memorizing the password because of the possibility of blinking and user’s high-speed input is another advantage of this system.

Details

Title
Eye gesture blink password: a new authentication system with high memorable and maximum password length
Author
Salehifar, Hananeh 1 ; Bayat, Peyman 1 ; Mojtaba Amiri Majd 2 

 Department of Computer Engineering, Rasht Branch, Islamic Azad University, Rasht, Iran 
 Department of Psychology, Abhar Branch, Islamic Azad University, Abhar, Iran 
Pages
16861-16885
Publication year
2019
Publication date
Jun 2019
Publisher
Springer Nature B.V.
ISSN
13807501
e-ISSN
15737721
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2162675936
Copyright
Multimedia Tools and Applications is a copyright of Springer, (2019). All Rights Reserved.