The Role of Visual Features in Text-Based CAPTCHAs: An fNIRS Study for Usable Security

Abstract

To mitigate dictionary attacks or similar undesirable automated attacks to information systems, developers mostly prefer using CAPTCHA challenges as Human Interactive Proofs (HIPs) to distinguish between human users and scripts. Appropriate use of CAPTCHA requires a setup that balances between robustness and usability during the design of a challenge. The previous research reveals that most usability studies have used accuracy and response time as measurement criteria for quantitative analysis. The present study aims at applying optical neuroimaging techniques for the analysis of CAPTCHA design. The functional Near-Infrared Spectroscopy technique was used to explore the hemodynamic responses in the prefrontal cortex elicited by CAPTCHA stimulus of varying types. The findings suggest that regions in the left and right dorsolateral and right dorsomedial prefrontal cortex respond to the degrees of line occlusion, rotation, and wave distortions present in a CAPTCHA. The systematic addition of the visual effects introduced nonlinear effects on the behavioral and prefrontal oxygenation measures, indicative of the emergence of Gestalt effects that might have influenced the perception of the overall CAPTCHA figure.

Figure 1

Example images generated for each single CAPTCHA feature.

Figure 2

The sequence of CAPTCHA stimuli displayed in one main block design.

Figure 3

Overall block design used in the experiment.

Figure 4

The projection of measurement locations (optodes) on a brain surface image (left), the light detectors and optodes identified on the fNIRS sensor (top-right), the flexible sensor pad placed over the forehead, and the control box (bottom-right).

Figure 5

Experiment setup.

Figure 6

Average accuracy percentages observed for the levels of line and wave when rotation was in off (a) and on (b) conditions. Error bars indicate %95 CI.

Figure 7

Average response times observed for the levels of line and wave when rotation was in off (a) and on (b) conditions. Error bars indicate %95 CI.

Figure 8

A B-spline interpolated projection of F-ratios corresponding to the three-way interaction effects observed for the HbO changes observed over the PFC.

Figure 9

Pearson correlation coefficients between average accuracy and average HbO changes observed at 16 different optodes for each CAPTCHA block type.

Figure 10

Pearson correlation coefficients between average accuracy and average HbR changes observed at 16 different optodes for each CAPTCHA block type.

Figure 11

Pearson correlation coefficients between average response times and average HbO changes observed at 16 different optodes for each CAPTCHA block type.

Figure 12

Pearson correlation coefficients between average response times and average HbR changes observed at 16 different optodes for each CAPTCHA block type.

Figure 13

Mean HbO change observed for line and wave conditions at optode 1 for rotation 1 (a) and rotation 2 (b) cases. Error bars indicate %95 CI.

Figure 14

Mean HbO change observed for line and wave conditions at optode 2 for rotation 1 (a) and rotation 2 (b) cases. Error bars indicate %95 CI.

Figure 15

Mean HbO change observed for line and wave conditions at optode 3 for rotation 1 (a) and rotation 2 (b) cases. Error bars indicate %95 CI.

Figure 16

Mean HbO change observed for line and wave conditions at optode 4 for rotation 1 (a) and rotation 2 (b) cases. Error bars indicate %95 CI.

Figure 17

Mean HbO change observed for line and wave conditions at optode 9 for rotation 1 (a) and rotation 2 (b) cases. Error bars indicate %95 CI.

Figure 18

Mean HbO change observed for line and wave conditions at optode 10 for rotation 1 (a) and rotation 2 (b) cases. Error bars indicate %95 CI.

Figure 19

Mean HbO change observed for line and wave conditions at optode 11 for rotation 1 (a) and rotation 2 (b) cases. Error bars indicate %95 CI.

Figure 20

Mean HbO change observed for line and wave conditions at optode 12 for rotation 1 (a) and rotation 2 (b) cases. Error bars indicate %95 CI.

Figure 21

Mean HbO change observed for line and wave conditions at optode 13 for rotation 1 (a) and rotation 2 (b) cases. Error bars indicate %95 CI.

Figure 22

Mean HbO change observed for line and wave conditions at optode 14 for rotation 1 (a) and rotation 2 (b) cases. Error bars indicate %95 CI.

Figure 23

Mean HbO change observed for line and wave conditions at optode 15 for rotation 1 (a) and rotation 2 (b) cases. Error bars indicate %95 CI.

Figure 24

Mean HbO change observed for line and wave conditions at optode 16 for rotation 1 (a) and rotation 2 (b) cases. Error bars indicate %95 CI.

Figure 25

Temporal HbO and HbR averages observed for the first 30 seconds of CAPTCHA blocks with difficulty level 1 for the line feature.

Figure 26

Temporal HbO and HbR averages observed for the first 30 seconds of CAPTCHA blocks with difficulty level 2 for the line feature.

Figure 27

Temporal HbO and HbR averages observed for the first 30 seconds of CAPTCHA blocks with difficulty level 3 for the line feature.

Figure 28

Temporal HbO and HbR averages observed for the first 30 seconds of CAPTCHA blocks with difficulty level 1 for the wave feature.

Figure 29

Temporal HbO and HbR averages observed for the first 30 seconds of CAPTCHA blocks with difficulty level 2 for the wave feature.

Figure 30

Temporal HbO and HbR averages observed for the first 30 seconds of CAPTCHA blocks with difficulty level 3 for the wave feature.

Figure 31

Temporal HbO and HbR averages observed for the first 30 seconds of CAPTCHA blocks with difficulty level 1 for the rotation feature.

Figure 32

Temporal HbO and HbR averages observed for the first 30 seconds of CAPTCHA blocks with difficulty level 2 for the rotation feature.