What Kind of Grid Formations and Password Formats are Useful for Password Authentication with Eye-Gaze-Based Input?

Yesaya T Paulus,Gerard B Remijn

doi:10.35248/2165-7556.19.9.249

Abstract

This study investigates which grid formations and password formats are useful for password authentication by means of eye-gazebased input. Sixteen grid formations were made, in between 3×3 to 6×6 cells (columns-by-rows), for three password formats. The formats were an alphanumeric format, a pattern format, and a picture format. The participants were asked to memorize a 4-object or a 6-object password and register (Task 1), confirm (Task 2), and log in (Task 4) the password on each of the 16 grids with eye-gaze-based input. In Task 3, the participants evaluated each grid with a rating scale. The results showed that task-completion time was mostly shorter for the alphanumeric password format than for the pattern or picture format. Task-completion time of 4-object or 6-object passwords generally increased as the grid density increased, while the task-success rate at the first attempt decreased when the grid density increased. Task-completion time often was longer for grids with more rows than columns (vertical formations, e.g., 3×4 cells) than for grids with more columns than rows (horizontal formations, e.g., 4×3 cells). These results suggest that password authentication with eye-gaze-based input is best performed on horizontal grids with relatively few cells and a traditional (alphanumeric) format.

Highlights

In recent years, a variety of password systems have been proposed as alternatives to the traditional text-based systems that require manual input of alphanumeric characters
In Task 3, preference data based on a rating scale for the password formats and grid formations were gathered
Since the data were not normally distributed, as confirmed with a Shapiro-Wilk test, non-parametric Friedman tests were performed in order to see whether task-completion time for all 16 grid formations varied with the password format

Summary

Introduction

A variety of password systems have been proposed as alternatives to the traditional text-based systems that require manual input of alphanumeric characters. Passwords can be made by drawing a figure on a grid, by indicating marker points on an image, or by selecting a sequence of symbols, patterns, or pictures from a display [2] The latter type of password systems involves the recognition of visual information. In a system called “Cued GazePoints” [7], the user can select points on a sequence of images, while holding the spacebar on a keyboard for a few seconds to record his/her gaze In both these password systems, compared with manual input only, the combination of a keyboard and eyegaze-based input is potentially safer against “shoulder-surfing” in public spaces, i.e., password theft by a third party who observes and copies a user’s manual input of digits or text. The authors reported that eye tracking would be a suitable and safe option for authentication, amongst others, on Automated Teller Machines (ATMs)

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