ACR Identifier for Privacy-Preserving Media Impression Tracking
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Solution Overview
Problem
Traditional methods for monitoring user access to Internet resources, such as server logs, are prone to errors due to tampering and cannot track cached content views, and audience measurement entities face challenges in accessing demographic data from database proprietors without compromising privacy, especially with the rise of mobile apps that do not use cookies.
Innovation Solution
The use of an Application Campaign Rating (ACR) identifier that encrypts device and user identifiers, allowing audience measurement entities to retrieve user information from partnered database proprietors while maintaining user privacy, by leveraging multiple database sources to create a large, demographically accurate panel for media impression tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If server logs are used to monitor user access to Internet resources, then the monitoring process is simple, but the data is prone to tampering and cannot track cached content views
Solution Approach 1:
The patent introduces a mediator component that sits between the content delivery system and the logging system. This mediator intercepts requests and responses, captures access information, and logs it in a tamper-resistant manner. The mediator validates cached content views by checking cache headers and logging these views separately from direct server accesses, thereby improving data reliability without significantly complicating the monitoring process.
2Measurement precision
If demographic data is accessed from database proprietors to improve audience measurement, then measurement accuracy improves, but user privacy may be compromised
Solution Approach 1:
The patent employs a mediator that acts as a privacy-protecting intermediary between the audience measurement system and database proprietors. The mediator receives anonymized device identifiers, matches them with demographic data from partnered databases, and returns only aggregated measurement results. This process allows accurate demographic-based measurement while preventing direct exposure of personal information, thus resolving the privacy-accuracy contradiction.
Solution Approach 2:
The system creates and uses anonymized copies of user identifiers (such as hashed device IDs) instead of accessing actual personal information. These copied identifiers can be matched with demographic data in database proprietor tables without revealing sensitive user details. The measurement system works with these anonymized copies throughout the process, ensuring accuracy while protecting privacy.
3Adaptability or versatility
If mobile apps that do not use cookies are monitored, then coverage of modern applications improves, but traditional cookie-based tracking methods become ineffective
Solution Approach 1:
The patent fundamentally changes the tracking parameter from cookie-based identifiers to device-level identifiers that are inherent to mobile devices (such as device IDs, advertising identifiers, or hardware-based identifiers). This parameter change allows the system to track mobile apps that do not use cookies, as the tracking is based on device characteristics rather than application-specific cookies. The system collects these device identifiers through app integration and uses them for consistent tracking across the app ecosystem.
Data Source
AI summary
Disclosed examples include accessing a search term from a client device; accessing a first identifier, the first identifier corresponding to a first database proprietor, the first identifier to access first user information corresponding to a user of the client device; accessing a second identifier, the second identifier corresponding to a second database proprietor, the second identifier to access second user information corresponding to the user of the client device; providing the search term, the first identifier, and the second identifier in a message; and transmitting the message to a server.