Overlay Human Interactive Proof System for Bot Differentiation
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Solution Overview
Problem
Existing human interactive proof systems (HIPs) are vulnerable to bots that have improved character recognition and image processing techniques, leading to unreliable differentiation between human and non-human users, necessitating a more secure method to grant access to computer-based resources.
Innovation Solution
An overlay human interactive proof system (OHIPS) generates a HIP by arranging visible objects, such as images, into predetermined regions and splitting them into partial images, which are then aligned by users to recognize correctly aligned visual objects, leveraging human ability to distinguish misaligned characters, and restricting motion to enhance security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional text-and image-based HIPs are used, then bots can pass the tests at high rates due to improved character recognition and image processing techniques, but the system becomes vulnerable to automated circumvention
Solution Approach 1:
The patent divides the image into multiple partial images that must be manually assembled or aligned by the user. This segmentation prevents automated character recognition and image processing from directly analyzing the complete image, as bots cannot easily reassemble fragmented pieces without human intervention
Solution Approach 2:
The patent introduces dynamic elements such as moving, rotating, or transforming partial images that change over time. This dynamic behavior makes it difficult for static or pre-processing-based bot systems to predict and circumvent the HIP, while humans can adapt and recognize the patterns dynamically
2Reliability
If HIPs are designed to be difficult for bots to pass, then security improves, but user convenience and ease of completion may deteriorate
Solution Approach 1:
The patent applies different levels of difficulty to different parts of the HIP. Some partial images or assembly steps are designed to be straightforward for humans, while others incorporate subtle distortions or require specific spatial reasoning. This localized variation ensures the overall system remains secure against bots while maintaining user-friendly completion
Data Source
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AI summary
Overlay human interactive proof system ("OHIPS") and techniques described herein operate in conjunction with any known or later developed computer-based applications or services to provide secure access to resources by reliably differentiating between human and non-human users. Humans have generally superior ability to differentiate misaligned characters or objects from correctly aligned ones. As such, the OHIP splits an image including one or more visual objects into two or more partial images to form a HIP. Partial images may also be further split into groups of sub-partial images, and/or partial images (or the sub-partial images) may be moved, so that at any given alignment position, a user can recognize only some visual objects. A user is instructed to reassemble the partial images at one or more predetermined alignment positions using a GUI, and the user is asked to identify information regarding one or more visible objects.