Title: Graphical passwords for older computer users

Authors: Nancy Carter; Cheng Li; Qun Li; Jennifer A. Stevens; Ed Novak; Zhengrui Qin

Addresses: Department of Computer Science, College of William & Mary, Williamsburg, VA 23187, USA ' Department of Computer Science, College of William & Mary, Williamsburg, VA 23187, USA ' Department of Computer Science, College of William & Mary, Williamsburg, VA 23187, USA ' Department of Psychological Sciences, College of William & Mary, Williamsburg, VA 23187, USA ' Department of Computer Science, Franklin & Marshall College, Lancaster PA 17604, USA ' School of Computer Science and Information Systems, Northwest Missouri State University, Maryville MO 64468, USA

Abstract: Traditional text password authentication is widely used to gain access to computing resources. Not all users possess the same cognitive and manual dexterity skills required to easily create, recall, and enter strong text passwords. We interviewed a group of older users, over the age of 60, and identified user challenges with recall and typing of strong text passwords. We developed and evaluated our graphical password user password system based on familiar facial images embedded randomly among unfamiliar, yet similar images. It assists older users through use of culturally familiar, and age-relevant images forming personalised password image sequences. Our usability study with 19 older volunteers measured recall, and timing with varying password image sequence lengths, increasing display complexity, and two input modalities, touchscreen and mouse. Our graphical password technique demonstrated a recall rate of 97%, password entropy superior to short PINs, and authentication time comparable to short text passwords.

Keywords: authentication; security; graphical passwords; human computer interaction; older users.

DOI: 10.1504/IJSN.2018.095170

International Journal of Security and Networks, 2018 Vol.13 No.4, pp.211 - 227

Available online: 31 Aug 2018 *

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