Dynamic Media Validation Questions Against AI Bot Probing
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Solution Overview
Problem
Existing captcha systems are vulnerable to automated bots due to predefined content and questions, which can be easily guessed by probing systems using artificial intelligence, and lack effective methods to engage user attention for media consumption.
Innovation Solution
A system that dynamically generates validation questions based on randomly selected media content items, such as images and videos, with corresponding questions curated at runtime, to create a dynamic captcha that engages user attention and makes it difficult for bots to breach.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If predefined content and questions are used in captcha, then the system is easier to implement and operate, but the system becomes vulnerable to automated bots that can guess the questions using artificial intelligence
Solution Approach 1:
The patent implements dynamic question generation based on media content attributes. Instead of using static predefined questions, the system generates questions at runtime by analyzing attributes of randomly selected media content items. This dynamic approach prevents bots from guessing questions in advance while maintaining operational simplicity through automated generation processes.
Solution Approach 2:
The system changes the parameters of questions by deriving them from various attributes of media content such as color, shape, size, position, and text. These parameter-based questions are generated dynamically, making each captcha instance unique and difficult for bots to predict, while the underlying generation mechanism remains consistent and easy to operate.
2Reliability
If probing systems use artificial intelligence to learn validation methods, then they can breach predefined captchas, but dynamically generated questions make it difficult for any probing system to guess or breach
Solution Approach 1:
The system performs self-service by automatically generating questions and determining answers based on media content attributes without requiring manual intervention. The automated generation process analyzes media content and creates unique questions with correct answers, reducing the need for human operators while enhancing security against AI probing through dynamic variability.
Solution Approach 2:
The media content serves multiple functions: it acts as both the validation challenge material and the source for generating questions. The same media content items are used to create questions, determine answers, and engage users, simplifying the system architecture while providing robust security through multi-purpose utilization of content.
3Productivity
If media content items are selected based on user profile, then user engagement and attention are improved, but the system requires more complex user data processing
Solution Approach 1:
The system performs preliminary actions by pre-selecting media content items based on user profiles before generating validation questions. User preferences and historical data are analyzed in advance to curate relevant media content, which then serves as the basis for question generation. This preliminary curation enhances user engagement while the automation of the process manages the complexity of data processing.
Data Source
AI summary
The system generates a validation tool in response to receiving an indication to initiate validation. The system identifies at least one media content item based on a user profile, and generates at least one question based on the at least one media content item. The at least one media content item may include an image, a video, text, or a combination thereof. The system determines at least one answer corresponding to the at least one question. The question and answer may be determined based on a question template. For example, the template may be selected based on attribute types or values of the at least one media content item. The system generates the at least one question for output on an output device. Upon receiving input indicative to an answer, the system compares the inputted answer to the determined answer to determine whether to validate the user.