BounTCHA: A CAPTCHA Utilizing Boundary Identification in Guided Generative AI-extended Videos
Lehao Lin, Ke Wang, Maha Abdallah, Wei Cai

TL;DR
BounTCHA is a new CAPTCHA system that uses boundary detection in AI-extended videos to differentiate humans from bots, leveraging human sensitivity to video transitions and disruptions.
Contribution
It introduces a novel CAPTCHA mechanism based on boundary identification in guided videos extended by generative AI, enhancing security against AI-bot attacks.
Findings
Humans are highly sensitive to video boundary shifts.
BounTCHA effectively distinguishes humans from bots.
Security analysis shows robustness against attacks.
Abstract
In recent years, the rapid development of artificial intelligence (AI) especially multi-modal Large Language Models (MLLMs), has enabled it to understand text, images, videos, and other multimedia data, allowing AI systems to execute various tasks based on human-provided prompts. However, AI-powered bots have increasingly been able to bypass most existing CAPTCHA systems, posing significant security threats to web applications. This makes the design of new CAPTCHA mechanisms an urgent priority. We observe that humans are highly sensitive to shifts and abrupt changes in videos, while current AI systems still struggle to comprehend and respond to such situations effectively. Based on this observation, we design and implement BounTCHA, a CAPTCHA mechanism that leverages human perception of boundaries in video transitions and disruptions. By utilizing generative AI's capability to extend…
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Taxonomy
TopicsUser Authentication and Security Systems · Innovative Human-Technology Interaction
