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This paper presents a real-world user study with over 3,600 unbiased (unwitting) participants solving over 9,000 reCAPTCHAv2 challenges. We explore four new dimensions of reCAPTCHAv2 solving time: # of attempts, service type, as well as educational level and major.
Abstract. Our work examines the efficacy of employing advanced machine learning methods to solve captchas from Google’s reCAPTCHAv2 system. We evaluate the effectiveness of automated systems in solving captchas by utilizing advanced YOLO models for image segmentation and classification.
1 sty 2023 · Invisible reCAPTCHA and some approaches have not yet been cracked. However, with the introduction of fourth generation bots accurately mimicking human behavior, a secure CAPTCHA would be hardly designed without additional special devices.
22 lip 2023 · In this work, we explore CAPTCHAs in the wild by evaluating users' solving performance and perceptions of unmodified currently-deployed CAPTCHAs.
9 sie 2023 · 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.
29 lut 2024 · Through case studies and success stories, we reveal the practical benefits of CAPTCHA implementation, showcasing its efficacy in diverse scenarios and underscoring its indispensable role in the modern digital landscape. Case Study 1: Automated Account Registration
The earliest CAPTCHAS asked users to transcribe random distorted text from an image. However, advances in computer vision and machine learning have dramatically increased the ability of bots to recognize distorted text [35,41,74], and by 2014, automated tools achieved over 99% accuracy [39, 62]. Alternatively, bots often outsource solving to ...
