Identity Fingerprint Matching for Cross-Device User Identification
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Solution Overview
Problem
Determining whether multiple computing devices, each with its own technical identifier, are associated with the same user is challenging, hindering the effective utilization of behavioral data across these devices.
Innovation Solution
An ad system maintains identity fingerprints and behavioral data for known computing entities, using non-unique parameters like IP address portions and User Agent data to identify candidate devices associated with a user, enabling the determination of relevant behavioral data for personalized advertising.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If each computing device uses its own technical identifier (IDFA, Advertising ID, cookies), then device identification is straightforward, but determining whether multiple devices belong to the same user becomes difficult
Solution Approach 1:
The patent introduces an intermediary approach by using identity fingerprints derived from non-unique parameters (IP address portions, User Agent data) as a mediator to connect multiple technical identifiers to the same user. Instead of directly matching unique device identifiers, the system creates a common reference (identity fingerprint) that can link multiple devices to a single user profile, thereby improving user identification accuracy without requiring direct comparison of complex unique identifiers.
Solution Approach 2:
The system transforms the identification approach by changing from using unique device parameters (IDFA, Advertising ID) to using non-unique parameters (IP address portions, User Agent data) that can be shared across multiple devices. This parameter change enables the creation of identity fingerprints that can match multiple devices to the same user, resolving the contradiction between accurate user identification and identifier complexity.
2Adaptability or versatility
If behavioral data is collected for each computing entity separately, then data privacy is maintained, but the ability to leverage behavioral data across devices for personalized advertising is impeded
Solution Approach 1:
The patent merges behavioral data from multiple computing entities by linking them through identity fingerprints. The system combines behavioral data associated with different technical identifiers (IDFA, Advertising ID, cookies) when those identifiers are linked to the same identity fingerprint, thereby creating a more complete user profile that can be used for personalized advertising while maintaining the original data collection structure.
Solution Approach 2:
The identity fingerprint serves as a universal key that can link multiple different technical identifiers and their associated behavioral data to a single user profile. This multi-functional approach allows the system to leverage behavioral data across different devices and identifiers without requiring a completely new data collection system, thereby improving behavioral data utilization while maintaining compatibility with existing privacy-preserving approaches.
3Adaptability or versatility
If non-unique parameters like IP address portions and User Agent data are used for identification, then linking multiple devices to the same user becomes feasible, but identification precision may be reduced due to parameter non-uniqueness
Solution Approach 1:
The patent segments the identification process into two levels: first, creating identity fingerprints from non-unique parameters to enable cross-device linking, and second, using these fingerprints to group devices under common user profiles. This segmentation allows the system to accept lower precision at the individual parameter level while achieving high accuracy at the user profile level by combining multiple data points.
Solution Approach 2:
The identity fingerprint acts as a composite identifier that combines multiple non-unique parameters (IP address portions, User Agent data) into a single matching key. Similar to composite materials that combine different properties to achieve superior characteristics, the composite identity fingerprint combines multiple weak identifiers to create a stronger, more reliable user identification mechanism that works across multiple devices.
Data Source
AI summary
Systems and methods for identifying one or more candidate computing entities associated with a first user of a first computing entity are disclosed. A first technical ID associated with the first computing entity and one or more parameters associated with the first computing entity are received by the ad system. A first identity fingerprint for the first computing entity is determined by the ad system. One or more candidate computing entities are identified by the ad system based on a similarity between the first identity fingerprint and an associated identity fingerprint of the one or more associated identity fingerprints of the candidate computing entity. First behavioral data is determined by the ad system based on the associated behavioral data of one or more of the one or more candidate computing entities. An advertisement based on the first behavioral data is provided by the ad system.