Anonymizing User Interactions via Group Segmentation
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Solution Overview
Problem
Existing interactive systems, such as those on the internet and mobile networks, often require user identification to provide personalized services, compromising user anonymity and privacy, while anonymous access prevents tailored responses and personalized experiences.
Innovation Solution
A method and apparatus that anonymize user interactions by assigning users to groups with similar characteristics, ensuring a minimum number of members in each group, and providing service providers with aggregated information to offer personalized services without revealing individual identities, using an information broker and clustering engine to manage group membership and interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If user identification is implemented to provide personalized services, then service personalization is improved, but user anonymity is compromised
Solution Approach 1:
The system segments users into groups based on shared characteristics (demographics, behavior patterns, preferences) rather than treating each user as an individual. This segmentation allows personalized services to be delivered to groups with similar profiles while maintaining individual anonymity, as the service provider only sees aggregated group data not specific user identities.
Solution Approach 2:
The system introduces an intermediary anonymization layer between the user and the service provider. This intermediary processes user data to extract characteristics for personalization while removing or masking identifying information. The service provider receives anonymized group assignments rather than direct user identifiers, enabling personalized service delivery without compromising user anonymity.
2Object-affected harmful factors
If anonymous access is provided to maintain user privacy, then user anonymity is improved, but service personalization capability deteriorates
Solution Approach 1:
The system changes the parameter of identification from specific user identifiers (IP addresses, device IDs) to aggregated group characteristics (demographic profiles, behavior patterns). This parameter transformation allows the system to maintain anonymity at the individual level while enabling personalization at the group level by matching services to characteristic profiles rather than specific users.
Solution Approach 2:
The system creates anonymized copies of user characteristics (demographics, preferences, behavior patterns) that can be used for service personalization without copying or exposing actual user identities. These characteristic copies enable personalized service delivery while the original identifying information remains protected and anonymous.
Data Source
AI summary
A method is provided of anonymizing an interaction between a user entity and a service provider node wishing to provide a service to the user entity in dependence upon characteristics of the user entity determined or revealed as a result of the interaction, the method comprising: assigning the user entity to at least one set, each set comprising as members a plurality of user entities sharing a characteristic associated with that set; ensuring that the intersection of the at least one set comprises at least a predetermined minimum number of user entities; and providing to the service provider node information relating to the or each characteristic associated with the at least one set, the information being for use at the service provider node in providing a service to the user entity that is appropriate in view of the characteristics of the user entity but insufficient to identify the user entity.