Page-Content Identifier Anonymization for Cross-Device Identity Resolution
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing tracking technologies face challenges in accurately and scalably tracking users across different devices and platforms due to the obsolescence of cookies and reliance on device-specific metadata, leading to reduced accuracy, increased error rates, and inefficient resource consumption.
Innovation Solution
Anonymizing unique identifiers extracted from page content, such as email addresses and credit card numbers, across multiple sessions to create pseudonymous identifiers that remain consistent across devices, and generating scores based on comparisons of these anonymized values to associate user sessions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If device-specific metadata and cookies are used for tracking users, then tracking capability is maintained, but accuracy and reliability deteriorate due to obsolescence and device-specific limitations
Solution Approach 1:
The patent introduces an intermediary mechanism using server-side processing and anonymized identifiers to mediate between user privacy requirements and tracking accuracy needs. The system extracts identifiers from page content, anonymizes them through hashing, and uses these pseudonymous identifiers for cross-session tracking, eliminating the need for direct user identification while maintaining tracking reliability.
Solution Approach 2:
The patent transforms tracking parameters from device-specific metadata and cookies to content-based anonymized identifiers. By changing the parameter basis from device-level to content-level identifiers and applying hashing algorithms, the system achieves both privacy preservation and accurate cross-device user tracking.
2Productivity
If cookies and device-specific tracking are used, then user tracking is possible, but scalability deteriorates due to platform limitations
Solution Approach 1:
The patent implements universality by extracting identifiers from page content that can be universally accessed across different devices and platforms. The anonymized identifiers serve multiple functions: they enable cross-session tracking, maintain user privacy, and work consistently across mobile and web applications without requiring device-specific configurations.
Solution Approach 2:
The system creates copies of user identifiers through anonymization processes. Instead of storing actual user data, the system generates hashed versions of identifiers extracted from page content, creating pseudonymous copies that can be safely shared and compared across different platforms while preserving user identity for tracking purposes.
3Measurement precision
If actual user identifiers are stored and processed, then tracking accuracy is improved, but security and privacy protection worsen
Solution Approach 1:
The patent extracts only the necessary identifier information from page content and immediately anonymizes it through hashing. By extracting only the minimal required data (identifiers from page content) and transforming them into pseudonymous forms, the system achieves tracking accuracy while eliminating the storage and processing of actual user identifiers, thus reducing security and privacy risks.
Solution Approach 2:
The system uses disposable anonymized identifiers that are generated fresh for each tracking operation. These hashed identifiers are temporary and cannot be reversed to obtain actual user data, creating a secure model where tracking accuracy is maintained through these short-lived pseudonymous objects rather than persistent storage of real user information.
Data Source
AI summary
Various embodiments discussed herein are directed to improving existing technologies by extracting or detecting identifiers from a page, regardless of the device or platform a user is using, and then anonymizing such identifiers to determine if the same user accessed different pages or if the current user of a current computer session is a same user as in past computer sessions.