Entity-to-Account Mapping for Anonymous Online Activity
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Solution Overview
Problem
The challenge in Internet communications is the ability for Internet users to remain virtually anonymous, making it difficult for website operators to initiate meaningful contact or marketing efforts, as they lack sufficient information to identify visitors beyond IP addresses, domains, and cookies.
Innovation Solution
A method using a generalized linear model to map anonymous Internet entities (IP addresses, domains, cookies) to known accounts by generating summary mappings, computing signal strengths, and selecting winning mappings based on credibility and time decay, with filters to refine the results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If Internet users maintain anonymity using IP addresses, domains, and cookies, then user privacy is protected, but the ability to initiate meaningful contact and marketing efforts is lost
Solution Approach 1:
The patent introduces an intermediary system that acts as a bridge between anonymous visitor data and marketing operations. The system uses summary mappings that aggregate visitor behavior patterns across multiple sessions and attributes, creating an intermediate representation that enables marketing initiatives without requiring direct identification of individual users. This intermediary layer processes anonymous data into actionable insights while preserving user anonymity.
2Measurement precision
If a system processes large volumes of online activity data to improve mapping accuracy, then de-anonymization effectiveness is improved, but processing time and computational resources increase
Solution Approach 1:
The patent segments the processing of online activity data by organizing it into discrete summary mappings that group related attributes and behavior patterns. Each summary mapping represents a condensed view of visitor activity across multiple dimensions, allowing the system to process and analyze data in manageable units rather than handling the entire dataset at once. This segmentation enables iterative processing and improves computational efficiency while maintaining mapping accuracy.
3Reliability
If the system generates multiple candidate mappings for each entity, then mapping reliability is improved, but the complexity of selecting and validating the best mapping increases
Solution Approach 1:
The patent implements feedback mechanisms that continuously refine mapping selections based on observed patterns and validation results. The system monitors the performance of generated mappings and uses this feedback to adjust the selection criteria and processing parameters. This feedback loop enables the system to learn from previous mappings and improve its accuracy over time while automating the selection process to reduce manual intervention and complexity.
Data Source
AI summary
The Internet generally provides anonymity to the online activities of visitors to web sites and other online resources. This prevents the operators of web sites and others from identifying visitors who do not wish to be identified. Accordingly, embodiments generate mappings between entities (e.g., IP addresses, domains, cookies, or devices) and accounts (e.g., companies) to de-anonymize online activities. In an embodiment, summary mappings are generated based on activity data. Each summary mapping may comprise an entity, potential account identifier, and an activity vector that measures observations of an association between the entity and potential account identifier from an activity source for multiple summary periods. A model may be applied to the summary mappings to compute signal strengths for a plurality of candidate mappings. A winning mapping may then be selected for each entity in the candidate mappings, and used to associate the entity with an account in one or more downstream functions.