Artificial Bid Requests for Detecting RTB User Data Misuse
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Solution Overview
Problem
Existing real-time bidding systems face issues with entities retaining and misusing user data beyond the scope of contractual agreements, leading to privacy concerns and unfair competition.
Innovation Solution
Implementing an artificial bid manager that generates and analyzes responses to artificial bid requests to detect inappropriate retention and misuse of user data by monitoring atypical bid patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detailed user information is provided to buyers for real-time bidding, then buyers can make informed bidding decisions, but user data is retained and misused beyond contractual agreements
Solution Approach 1:
The system performs preliminary actions by providing detailed user information to buyers for making informed bidding decisions, while simultaneously implementing detection mechanisms before data misuse can occur. The artificial bid manager proactively monitors and analyzes bidding patterns to prevent privacy violations before they happen.
Solution Approach 2:
The system implements feedback mechanisms where the artificial bid manager continuously monitors bidding data and provides feedback to detect potential misuse. By analyzing bidding patterns and comparing them against expected behavior, the system can identify and alert on potential privacy violations, creating a closed-loop feedback system that protects user data while maintaining bidding effectiveness.
2Quantity of substance
If buyers retain user data for secondary uses, then data can be leveraged for additional business value, but contractual agreements are violated and fair competition is compromised
Solution Approach 1:
The artificial bid manager acts as an intermediary between data usage and contractual compliance. It monitors and analyzes bidding patterns to ensure that data utilization remains within agreed-upon boundaries. The system mediates between the desire to leverage data for business value and the need to maintain contractual integrity, allowing legitimate data use while preventing misuse.
Solution Approach 2:
The system replaces manual compliance monitoring with an automated artificial intelligence-based bid manager. This mechanical substitution enables continuous, scalable monitoring of data usage patterns without requiring human intervention, allowing the system to handle large volumes of bidding data while maintaining contractual compliance through automated detection and alerting mechanisms.
3Reliability
If an artificial bid manager monitors all bidding data, then data misuse can be detected, but system complexity increases
Solution Approach 1:
The system extracts only the essential monitoring functions needed to detect data misuse, rather than implementing a comprehensive analysis of all bidding data. The artificial bid manager focuses on identifying specific patterns indicative of misuse, separating the critical detection functions from the overall bidding system. This extraction approach maintains reliability while minimizing the added complexity by concentrating on key detection capabilities.
Data Source
AI summary
Embodiments of the present invention are directed to detecting misuse of contextual data, such as user data. In accordance with some embodiments of the present invention, artificial contextual data is created for artificial users and is, thereafter, provided to a bidder(s). Based on reception of artificial contextual data, bidders can place bids for presentation of advertisements. Bids placed by bidders receiving such artificial context data can be collected and analyzed. When bids appear to be atypically increased or decreased based on the artificial contextual data, a determination can be made that the bidder retains and/or misuses contextual data, such as user data.