{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T15:30:14Z","timestamp":1781105414794,"version":"3.54.1"},"reference-count":30,"publisher":"IGI Global Scientific Publishing","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2012,4,1]]},"abstract":"<p>Many web-based services such as email, search engines, and polling sites are being abused by spammers via computer programs known as bots. This problem has bred a new research area called Human Interactive Proofs (HIP) and a testing device called CAPTCHA, which aims to protect services from malevolent attacks by distinguishing bots from human users. In the past decade, researchers have focused on developing robust and safe HIP systems but have barely evaluated their usability. To begin to fill this gap, the authors report the results of a user study conducted to determine the extent that English language proficiency affects CAPTCHA usability for users whose native language is not English. The results showed a significant effect of participants\u2019 English language proficiency level on the time the participant takes to solve CAPTCHA, which appear to be related to multiple usability issues including satisfaction and efficiency. Yet, they found that English language proficiency level does not affect the number of errors made while entering CAPTCHA or reCAPTCHA. The authors\u2019 results have numerous implications that may inform future CAPTCHA design.<\/p>","DOI":"10.4018\/jwp.2012040105","type":"journal-article","created":{"date-parts":[[2012,12,26]],"date-time":"2012-12-26T11:35:02Z","timestamp":1356521702000},"page":"74-87","source":"Crossref","is-referenced-by-count":6,"title":["Script Familiarity and Its Effect on CAPTCHA Usability"],"prefix":"10.4018","volume":"4","author":[{"given":"Ashraf","family":"Khalil","sequence":"first","affiliation":[{"name":"College of Engineering and Computer Science, Abu Dhabi University, UAE"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Salam","family":"Abdallah","sequence":"additional","affiliation":[{"name":"College of Business Administration, Abu Dhabi University, UAE"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Soha","family":"Ahmed","sequence":"additional","affiliation":[{"name":"College of Engineering and Computer Science, Abu Dhabi University, UAE"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hassan","family":"Hajjdiab","sequence":"additional","affiliation":[{"name":"College of Engineering and Computer Science, Abu Dhabi University, UAE"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"jwp.2012040105-0","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2010.31"},{"key":"jwp.2012040105-1","first-page":"17","article-title":"Using machine learning to break visual human interaction proofs (HIPs).","author":"K.Chellapilla","year":"2004","journal-title":"Advances in Neural Information Processing Systems"},{"key":"jwp.2012040105-2","doi-asserted-by":"crossref","unstructured":"Chow, R., Golle, P., Jakobsson, M., Wang, L., & Wang, X.-F. 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