An Empirical Study & Evaluation of Modern CAPTCHAs


Andrew Searles, University of California, Irvine; Yoshimichi Nakatsuka, ETH Zürich; Ercan Ozturk, University of California, Irvine; Andrew Paverd, Microsoft; Gene Tsudik, University of California, Irvine; Ai Enkoji, Lawrence Livermore National Laboratory


For nearly two decades, CAPTCHAS have been widely used as a means of protection against bots. Throughout the years, as their use grew, techniques to defeat or bypass CAPTCHAS have continued to improve. Meanwhile, CAPTCHAS have also evolved in terms of sophistication and diversity, becoming increasingly difficult to solve for both bots (machines) and humans. Given this long-standing and still-ongoing arms race, it is critical to investigate how long it takes legitimate users to solve modern CAPTCHAS, and how they are perceived by those users.

In this work, we explore CAPTCHAS in the wild by evaluating users' solving performance and perceptions of unmodified currently-deployed CAPTCHAS. We obtain this data through manual inspection of popular websites and user studies in which 1,400 participants collectively solved 14,000 CAPTCHAS. Results show significant differences between the most popular types of CAPTCHAS: surprisingly, solving time and user perception are not always correlated. We performed a comparative study to investigate the effect of experimental context – specifically the difference between solving CAPTCHAS directly versus solving them as part of a more natural task, such as account creation. Whilst there were several potential confounding factors, our results show that experimental context could have an impact on this task, and must be taken into account in future CAPTCHA studies. Finally, we investigate CAPTCHA-induced user task abandonment by analyzing participants who start and do not complete the task.

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@inproceedings {291062,
author = {Andrew Searles and Yoshimichi Nakatsuka and Ercan Ozturk and Andrew Paverd and Gene Tsudik and Ai Enkoji},
title = {An Empirical Study \& Evaluation of Modern {CAPTCHAs}},
booktitle = {32nd USENIX Security Symposium (USENIX Security 23)},
year = {2023},
isbn = {978-1-939133-37-3},
address = {Anaheim, CA},
pages = {3081--3097},
url = {},
publisher = {USENIX Association},
month = aug

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