A study of cognitive process of text-based CAPTCHA tasks by eye-tracking data

• Main Authors: Jui-Chia Ma, 馬瑞家
• Other Authors: Ying-Lien Lee
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/04968580736239851052

碩士 === 朝陽科技大學 === 工業工程與管理系碩士班 === 100 === Abstract CAPTCHA, the acronym of “Completely Automatic Public Turning test to tell Computers and Human Apart”, is kind of security measures for preventing hacker to overuse the internet service and resource. However, text-based CAPTCHA is the most common security measure but this way also could be deciphered by computer program. Therefore, text-based CAPTCHA must add the disturbance on the design to cause the computer program could not easy to recognize, but the excessive disturbance design will possibly increase the identification visual and cognition loading when user is trying to recognize something. Currently, OCR software can tell text-based CAPTCHA by using dictionary function so that the general designs of text-based CAPTCHA are word and non-word for users’ identification. In the course of cognition, we find that the familiar words are in a process from top-down with rapid reaction speed. However, compared to non-word visual system, it must form these stimulated analyses into a character in the process from bottom-up and the speed is slow. Word and non-word are treated as the first experimental factor based on the above reasons. The previous research has compared with the reactive time of text-based CAPTCHA and finds the difficult text-based CAPTCHA is related with the theory proposed in the occluded object recognition research. The foreground objects of covered characters are visible and belong to Thread Noise. If the foreground object is the reverse type, it is invisible and belongs to Line Mask. If foreground object is neither the object nor reverse type, it is incoherent and belongs to Blot Mask. The above three kinds of interferences are treated as the second experimental factor. This research discusses the cognitive process of these factor groups and observes subjects’ eye-tracking data through the eye tracker as well as compares subjects’ difference among working performance, visual fatigue, workload and cognitive process in different groups’ text-based CAPTCHA. The research results show incoherence cuts response time obviously and the error rate is lower. Moreover, word combination helps to improve the identification performance of the subject and is effective in reducing the fatigue in visual sense. However, invisible interference design can affect the eye-tracking data of each character, easily increasing the load of visual sense. The bottom-up processing in text reading and cognition will not only increase the load of users in identification, but even make trouble for users. We suggest that designers of text-based CAPTCHA collocate incoherence with non-word combination, and collocate visibility with word combination. It is effective in both preventing text-based CAPTCHA being cracked and reducing the load of identification in cognition processing so as to enhance users’ passing rate.