User Agent Mapping for Client Device Identification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing audience measurement systems face challenges in accurately identifying client devices due to MAC address randomization and other obfuscation techniques, leading to inaccurate media exposure data and hindered advertising/media inventory optimization.
Innovation Solution
A method and system that maps user agents in network traffic data to device identifiers using an audience measurement database, bypassing MAC address randomization by comparing user agent attributes with candidate device attributes and determining a confidence score based on occurrence frequency, thereby accurately identifying client devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If MAC address randomization and obfuscation techniques are used to protect device privacy, then device identification accuracy deteriorates, but media exposure measurement reliability is compromised
Solution Approach 1:
The patent introduces an intermediary mapping system that connects user agents to device identifiers through a database of device attributes. Instead of directly using MAC addresses for identification, the system uses user agents as intermediaries to establish mappings to device identifiers, thereby bypassing the obfuscation problem while maintaining identification accuracy.
Solution Approach 2:
The patent changes the identification parameter from MAC address to user agent. By using user agents (which contain browser and device information) instead of MAC addresses, the system can identify devices without being affected by MAC randomization and obfuscation techniques, thus resolving the contradiction between privacy protection and identification accuracy.
2Measurement precision
If traditional device identification methods are used, then media exposure data can be collected, but computational resources are excessive and accuracy is reduced
Solution Approach 1:
The patent extracts only the necessary information from network traffic data - specifically the user agent string - and maps it to device identifiers using a pre-established database. This extraction approach eliminates the need to process entire network traffic datasets computationally intensive ways, reducing resource consumption while maintaining measurement precision.
Solution Approach 2:
The system performs preliminary action by pre-establishing mappings between user agents and device identifiers in a database. This preliminary mapping allows for efficient lookup during media exposure measurement without requiring complex real-time computational analysis, thus reducing computational resource requirements while maintaining accuracy.
3Reliability
If user agent mapping to device identifiers is implemented, then device identification accuracy improves, but system complexity increases
Solution Approach 1:
The patent creates a simplified copy of the device identification process. Instead of complex real-time analysis of network traffic to identify devices, the system uses pre-computed mappings stored in a database. This copying approach simplifies the measurement system by replacing complex computational processes with simple lookup operations, thus reducing system complexity while maintaining identification accuracy.
Data Source
AI summary
In one example, a method is described. The method includes: obtaining network traffic data including at least one user agent, where the user agent is associated with a client device coupled to a network at a media exposure measurement location, and where the user agent comprises a string of characters defining client device attributes, comparing one or more of the client device attributes to candidate device attributes stored in an audience measurement database, based on the comparison, selecting, from a set of candidate device attributes, a set of target device attributes corresponding to a target device identifier, determining a number of occurrences of the set of target device attributes in the network traffic data, and based on a determination that the number of occurrences is above a threshold, outputting the target device identifier as the device identifier that corresponds to the user agent.