Andrew Searles (University of California Irvine), Renascence Tarafder Prapty (University of California Irvine), Gene Tsudik (University of California Irvine)

Since 2003, CAPTCHAS have been widely used as a barrier against bots, while simultaneously annoying great multitudes of users worldwide. As the use of CAPTCHAS grew, techniques to defeat or bypass them kept improving. In response, CAPTCHAS themselves evolved in terms of sophistication and diversity, becoming increasingly difficult to solve for both bots and humans. Given this long-standing and still-ongoing arms race, it is important to investigate usability, solving performance, and user perceptions of modern CAPTCHAS. In this work, we do so via a large scale (over 3,600 distinct users) 13-month realworld user study and post-study survey. The study, conducted at a large public university, is based on a live account creation and password recovery service with currently prevalent CAPTCHA type: reCAPTCHAv2.

Results show that, with more attempts, users improve in solving checkbox CAPTCHAS. For website developers and user study designers, results indicate that the website context, i.e., whether the service is password recovery or account creation, directly influences (with statistically significant differences) CAPTCHA solving times. We consider the impact of participants’ major and education level, showing that certain majors exhibit better performance, while, in general, education level has a direct impact on solving time. Unsurprisingly, we discover that participants find image CAPTCHAS to be annoying, while checkbox CAPTCHAS are perceived as easy. We also show that, rated via System Usability Scale (SUS), image CAPTCHAS are viewed as “OK”, while checkbox CAPTCHAS are viewed as “good”.

Finally, we also explore the cost and security of reCAPTCHAv2 and conclude that it comes at an immense cost and offers practically no security. Overall, we believe that this study’s results prompt a natural conclusion: reCAPTCHAv2 and similar reCAPTCHA technology should be deprecated.

View More Papers

Off-Path TCP Hijacking in Wi-Fi Networks: A Packet-Size Side...

Ziqiang Wang (Southeast University), Xuewei Feng (Tsinghua University), Qi Li (Tsinghua University), Kun Sun (George Mason University), Yuxiang Yang (Tsinghua University), Mengyuan Li (University of Toronto), Ganqiu Du (China Software Testing Center), Ke Xu (Tsinghua University), Jianping Wu (Tsinghua University)

Read More

Secure Data Analytics in Apache Spark with Fine-grained Policy...

Byeongwook Kim (Seoul National University), Jaewon Hur (Seoul National University), Adil Ahmad (Arizona State University), Byoungyoung Lee (Seoul National University)

Read More

IsolateGPT: An Execution Isolation Architecture for LLM-Based Agentic Systems

Yuhao Wu (Washington University in St. Louis), Franziska Roesner (University of Washington), Tadayoshi Kohno (University of Washington), Ning Zhang (Washington University in St. Louis), Umar Iqbal (Washington University in St. Louis)

Read More