Entropy Cap User Group Assignment for Application Experiment Anonymity
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Solution Overview
Problem
Conducting experiments on applications can lead to users being uniquely identifiable due to the assignment of unique experimental variations, especially when the number of users is low or the number of experiments is high, which compromises user anonymity.
Innovation Solution
Implementing an entropy cap to limit the user group numbers, ensuring that multiple users can share the same state, thereby reducing the risk of unique identification by randomly assigning user group numbers and experimental variations based on these numbers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple experiments with multiple variations are conducted on a population of users, then the ability to test and improve the application is enhanced, but the risk of uniquely identifying individual users increases
Solution Approach 1:
The patent segments users into groups based on entropy cap constraints, where each user is assigned a user group number that limits the total number of distinct experimental states. This segmentation ensures that users are distributed across a limited number of groups, preventing unique identification while still allowing multiple experiments to be conducted. The entropy cap parameter controls the segmentation granularity to balance experiment versatility with anonymity protection.
2Productivity
If the number of experiments is increased to improve application performance, then more variations can be tested, but fewer users may be uniquely identifiable
Solution Approach 1:
The patent introduces the entropy cap as a controlling parameter that limits the expected entropy of user assignments across experiments. By adjusting this parameter, the system can control the trade-off between conducting more experiments (productivity) and maintaining user anonymity (reliability). The entropy cap constrains the total information content about user assignments, ensuring that even with multiple experiments, individual users cannot be uniquely identified.
3Object-affected harmful factors
If user group numbers are randomly assigned to ensure anonymity, then user identification risk is reduced, but the precision of experimental assignment may be compromised
Solution Approach 1:
The patent implements a dynamic assignment system where user group numbers are randomly assigned within the constraints of the entropy cap. This dynamic randomization ensures that user assignments change based on probabilistic rules rather than fixed patterns, maintaining anonymity while still allowing for controlled experimental variations. The system adapts assignments to satisfy both anonymity requirements and experimental precision needs through the entropy cap constraint.
Data Source
AI summary
Systems and methods for conducting a set of experiments on an application having a plurality of users are provided. Each experiment is identified by a respective experiment identification (ID) and is associated with a respective group of experimental variations of the application. A system includes an entropy source module that assigns a user group number to a designated user. The user group number is less than or equal to an entropy cap, which is less than an expected entropy, which represents a total number of different states of the experiments. The system includes an experiment module that determines a designated one of the experiments to be conducted on the application. The designated experiment is identified by a designated experiment ID and is associated with a designated group of experimental variations of the application. The experiment module assigns a designated variation to the designated user based on the user group number.