Consent Management System Automated Rejection Filtering
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Solution Overview
Problem
Automated consent rejection tools complicate the process of obtaining valid user consent for tracking tools, as they can simulate user interactions, making it difficult to distinguish between human and automated denials, leading to resource wastage and inefficiencies in consent processing.
Innovation Solution
A consent management system that differentiates between human and automated consent rejections by analyzing function call attributes, such as timing, frequency, and token presence, and requires additional confirmation through interfaces like CAPTCHA to ensure valid human input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated consent rejection tools are used to automatically reject tracking tool requests, then consent processing efficiency is improved, but the reliability of consent data deteriorates because the system cannot distinguish between human and automated denials
Solution Approach 1:
The patent introduces an intermediary verification mechanism (CAPTCHA challenge) between the consent rejection function call and the final consent data recording. When an automated tool detects a function call pattern suggesting automation, it triggers a CAPTCHA challenge that only human users can complete, thereby filtering out automated rejections while preserving legitimate human consent decisions.
Solution Approach 2:
The system performs preliminary analysis of function call attributes (timing, frequency, pattern recognition) before recording consent data. This preliminary detection of automated tool usage allows the system to preemptively challenge or reject automated consent attempts before they contaminate the consent database, ensuring data reliability while maintaining processing efficiency for legitimate users.
2Speed
If the system processes all consent rejection function calls without verification, then processing speed is maintained, but resource wastage increases due to handling automated tool rejections
Solution Approach 1:
The system implements feedback loops that monitor consent rejection patterns and automatically adjust processing behavior. When automated tool patterns are detected through function call analysis, the system feeds this information back to modify subsequent processing, challenging or rejecting automated calls without requiring full human verification, thereby conserving resources while maintaining speed for legitimate requests.
Solution Approach 2:
The system dynamically changes processing parameters based on detected function call characteristics. For calls exhibiting automated patterns (unusual timing, frequency, or sequence), the system adjusts verification thresholds and challenge requirements, thereby optimizing resource allocation by applying intensive verification only when necessary while maintaining high-speed processing for normal human interactions.
3Reliability
If additional verification steps like CAPTCHA are implemented to distinguish human from automated users, then consent data reliability is improved, but device complexity increases
Solution Approach 1:
The verification system is segmented into multiple independent modules: function call pattern analysis, automated tool detection engine, CAPTCHA challenge generation, and consent data validation. This segmentation allows each component to perform its specific function independently, making the overall complex system more manageable, maintainable, and scalable while achieving high reliability through coordinated operation of specialized subsystems.
Data Source
AI summary
Various aspects involve forgoing updates to consent data for at least one consent rejection generated by an automated consent rejection tool. For instance, a consent management system can be communicatively coupled to a user device. The user device can detect invocations of a consent rejection function, such as when browser states of a browser application indicate requests for web pages or other online content. The consent management system can document a consent rejection for one or more of the invocations. The consent management system can also prevent documentation of consent being rejected for at least one invocation initiated by an automated consent rejection tool.