Identity Management System Using Profile Data Mining for Familiar Claims Provider Selection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing identity management systems are often cumbersome or non-intuitive for users, leading to mistrust and poor adoption, while also potentially allowing companies to track individuals' online activities, compromising privacy.
Innovation Solution
The system mines profile data to identify familiar claims providers and presents a candidate set of both user-familiar and relying-party-allowed claims providers, enabling users to select suitable claims without revealing unnecessary information, thereby maintaining privacy and improving user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If secure identity management systems are implemented, then security and reliability are improved, but user experience and ease of operation deteriorate due to cumbersome processes
Solution Approach 1:
The system automatically mines profile data from multiple sources (social media, browsing history, purchase history) to generate candidate claims providers without requiring user input. The user simply selects from pre-generated options, making the secure identity verification process self-service and intuitive.
Solution Approach 2:
The system performs preliminary actions by proactively gathering profile data and identifying familiar claims providers before the user needs to authenticate. This pre-computation eliminates the need for users to manually search for or configure security settings during the authentication process.
2Reliability
If traditional identity management systems are used, then security is maintained, but privacy is compromised due to tracking of user activities
Solution Approach 1:
The system applies local quality by allowing different claims providers to be selected for different contexts or services. Users can grant fine-grained control over which aspects of their identity are verified by which providers, enabling security for specific services while maintaining privacy in other areas.
Solution Approach 2:
The system segments the identity verification process into multiple independent claims providers, each handling specific types of claims. This segmentation allows users to selectively engage only the necessary providers for each service, preventing comprehensive tracking while maintaining security where needed.
3Measurement precision
If comprehensive profile data is collected, then accuracy of identifying familiar claims providers is improved, but processing time and system complexity increase
Solution Approach 1:
The system uses partial action by collecting only the specific profile data elements needed to identify familiar claims providers (such as browsing history related to specific services or social media connections), rather than comprehensively analyzing all user data. This selective approach maintains accuracy while reducing processing time.
Data Source
AI summary
Aspects of the subject matter described herein relate to identity technology. In aspects, profile data is mined to determine claims providers with which a user may be familiar. These familiar claims providers are used in conjunction with claims providers that are allowed by a relying party to determine a candidate set of claims providers that are both familiar to the user and allowed by the relying party. This candidate set of claims providers is then displayed to a user so that the user may select one or more of the claims providers to obtain claims to provide to the relying party.