Animation-Based CAPTCHA Distinguishing Human From Machine Input
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Solution Overview
Problem
Current CAPTCHAs, such as image-based and text-based challenges, are increasingly vulnerable to automated attacks due to advancements in artificial intelligence and machine learning, allowing bots to bypass security measures and access web services, leading to malicious activities and resource wastage in identifying and mitigating security breaches.
Innovation Solution
A human authentication platform generates a human authentication challenge using animations with multiple frames, requiring users to interpret the sequence of images, which is difficult for bots trained on static images to complete, thereby distinguishing human from machine input and enhancing security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If static image-based CAPTCHAs are used, then implementation is simple and fast, but security is weakened due to AI/ML advancements allowing bots to bypass them
Solution Approach 1:
The patent transforms the CAPTCHA challenge from static images to animated sequences, changing the temporal parameter from stationary to dynamic. This parameter change makes the challenge resistant to AI/ML models trained on static images while maintaining visual accessibility for human users.
Solution Approach 2:
The patent introduces motion and temporal sequencing to the CAPTCHA challenge by using animated GIFs with multiple frames. This dynamic approach contrasts with traditional static image CAPTCHAs and creates a challenge that requires processing temporal information, which is more difficult for automated systems.
2Reliability
If animation-based CAPTCHAs requiring frame sequence interpretation are used, then security is improved, but processing time and computational resources increase
Solution Approach 1:
The patent requires users to interpret only the sequence of actions depicted in the animation rather than analyzing every frame in detail. This partial action approach maintains security by requiring temporal understanding while reducing the cognitive load and processing time compared to full frame-by-frame analysis.
Data Source
AI summary
A device may obtain an animation, wherein the animation comprises a set of frames to emulate a moving image. The device may obtain a label to associate with the animation. The device may generate a human authentication challenge, wherein the human authentication challenge includes a display using the animation, and directions for a user to complete a task by interpreting the animation. The device may generate instructions to cause a user device to display the human authentication challenge. The device may send, to the user device, the instructions to cause the user device to display the human authentication challenge. The device may receive an input to the human authentication challenge regarding the animation. The device may analyze the input using the label to determine whether to authenticate the user. The device may perform an action based on analyzing the input using the label to determine whether to authenticate the user.