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Automated CAPTCHA Generation Using Machine Learning For Image And Audio Challenges
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Advancements in CAPTCHA design are reshaping digital security and accessibility. This study introduces an adaptive system that evaluates audio, text-based, and emerging CAPTCHA formats to balance usability and protection against bots. A key focus is SoundsRight, an audio CAPTCHA aiding visually impaired users by using sound recognition amidst noise. User trials revealed improved security but longer response times, highlighting usability trade-offs. Text-based CAPTCHAs tested on tablets showed performance variations based on demographics like age and experience. Additional formats—image, gesture, logic, and gamified—were assessed for inclusivity and effectiveness. Results support hybrid CAPTCHA systems that adapt to diverse user needs, ensuring broader accessibility without compromising security
Title: Automated CAPTCHA Generation Using Machine Learning For Image And Audio Challenges
Description:
Advancements in CAPTCHA design are reshaping digital security and accessibility.
This study introduces an adaptive system that evaluates audio, text-based, and emerging CAPTCHA formats to balance usability and protection against bots.
A key focus is SoundsRight, an audio CAPTCHA aiding visually impaired users by using sound recognition amidst noise.
User trials revealed improved security but longer response times, highlighting usability trade-offs.
Text-based CAPTCHAs tested on tablets showed performance variations based on demographics like age and experience.
Additional formats—image, gesture, logic, and gamified—were assessed for inclusivity and effectiveness.
Results support hybrid CAPTCHA systems that adapt to diverse user needs, ensuring broader accessibility without compromising security.
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