On-Device Privacy-Preserving Exposure Attribution for Mobile Tracking
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Solution Overview
Problem
Existing methods for attribution and exposure tracking in mobile devices compromise user privacy by requiring access to and storage of personally identifiable location data, which can lead to unwanted tracking and abuse.
Innovation Solution
Implementing a system where attribution and exposure determination are performed on-board the mobile device, with results communicated remotely without sharing specific locations or identifiers, using cryptography and non-fungible tokens to ensure privacy and anonymity, and allowing on-device computation to protect sensitive information like MAID, longitude, and latitude.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If location data and identifiers are accessed and stored to provide attribution services, then attribution accuracy is improved, but user privacy is compromised and tracking abuse risks increase
Solution Approach 1:
The patent extracts the attribution calculation function from the server and places it on the mobile device itself. The device performs calculations using its own location data without needing to transmit or store this sensitive data on remote servers, thereby maintaining attribution accuracy while eliminating the privacy risks associated with centralized data storage.
Solution Approach 2:
The mobile device serves itself by performing attribution calculations locally using its own location history and the provided job parameters. The device independently determines exposure and visitation data without requiring server access to its private location information, thus maintaining privacy while achieving accurate attribution.
2Adaptability or versatility
If huge amounts of location data are stored to facilitate attribution, then attribution capability is improved, but device complexity and data management burden increase
Solution Approach 1:
The patent segments the attribution process into discrete computational steps that the mobile device executes locally. Instead of managing and processing huge amounts of raw location data, the device receives job parameters, performs specific calculations using its location history, and returns only the necessary attribution results, significantly reducing data management complexity.
Solution Approach 2:
The mobile device pre-stores its location history and travel path data locally, preparing this information in advance for attribution calculations. When attribution jobs are received, the device can quickly perform calculations using the pre-existing location data without needing to retrieve or manage large datasets in real-time, reducing operational complexity.
3Ease of operation
If travel path and location identifiers are transmitted to servers for processing, then attribution services are enabled, but privacy security is compromised
Solution Approach 1:
The patent extracts the sensitive location data processing from the server environment and performs it entirely on the mobile device. The device receives attribution jobs, executes calculations using its local location history, and returns only the necessary results without transmitting any personal location information, thereby maintaining service availability while ensuring privacy security.
Solution Approach 2:
The mobile device acts as an intermediary between the user's location data and the attribution service requirements. It receives job parameters, performs necessary calculations using its own location history, and returns aggregated attribution results without exposing the underlying location data, thus mediating between service needs and privacy protection.
Data Source
AI summary
For privacy-preserving attribution, the exposure and/or attribution to physical media (e.g., a surface or object) is determined on-board the mobile device. The exposure and/or attribution may be communicated remotely from the mobile device without passing specific locations and/or identifiers of the operator. The attribution information may be used by others without having access to private information, which never leaves the mobile device.