Identity Attribute Alteration via Rules Engine
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Solution Overview
Problem
Existing systems for verifying and altering user identities in networks often fail due to errors in physical documents, such as extraction errors or formatting issues, leading to verification failures and lack of options for correcting these errors.
Innovation Solution
The system allows users to alter identity attributes by modeling edit rules based on historical data and employing a rules engine to identify and adapt legitimate changes while preventing illegitimate alterations, using a combination of physical documents and digital verification processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users are allowed to alter identity attributes freely, then correction of errors in physical documents is enabled, but risk of identity theft and illegitimate alterations increases
Solution Approach 1:
The system changes the parameters of attribute alteration by implementing edit rules that define specific conditions under which attributes can be modified. These rules control aspects such as the number of allowable edits, types of permissible changes, and require supporting documentation, thereby enabling error correction while maintaining security through parameterized control mechanisms.
Solution Approach 2:
The system introduces an intermediary rules engine that mediates between users and identity attribute alterations. This intermediary evaluates edit requests against predefined rules, determines whether alterations are legitimate, and enforces constraints on modifications. The rules engine acts as a mediator that enables necessary corrections while preventing illegitimate changes through automated decision-making.
2Reliability
If strict verification rules are applied to prevent identity theft, then security is improved, but ability to correct legitimate errors is reduced
Solution Approach 1:
The system implements dynamic verification rules that adapt based on the specific context of each attribute alteration request. The rules engine evaluates multiple factors including the type of attribute being changed, the user's verification history, the nature of the error being corrected, and the strength of supporting documentation. This dynamic approach allows the system to be strict when necessary for security while being more permissive when legitimate errors are being corrected.
Solution Approach 2:
The system applies different verification strictness levels to different identity attributes based on their sensitivity and error-proneness. Critical attributes like date of birth or government ID numbers may have stricter alteration rules requiring additional verification, while less critical attributes may allow more flexible corrections. This local quality approach ensures security for high-risk attributes while enabling error correction for lower-risk attributes.
3Productivity
If automated rules engine is used to evaluate attribute changes, then processing speed is improved, but complexity of the system increases
Solution Approach 1:
The system segments the verification process into distinct modular components: attribute extraction from physical documents, validation against edit rules, determination of legitimacy, and execution of alterations. Each component is independently implemented and can be processed automatically. This segmentation enables the rules engine to evaluate changes through a series of discrete, manageable steps rather than a monolithic complex process, improving automated processing while organizing complexity into manageable modules.
Data Source
AI summary
Systems and methods are provided for changing attributes of user identities based on event driven rules. One example computer-implemented method includes receiving, at a computing device, from a mobile device, identification information associated with enrollment of an identity attribute of a user to a digital identity for the user and also receiving, from the mobile device, a request for a change to the identity attribute of the digital identity of the user. The method also includes determining a rule applicable to the change of the identity attribute based on a type of the identity attribute and/or a source of the identity attribute and determining whether the change to the at least one identity attribute is consistent with the rule. And, the method then includes effecting the change to the at least one identity attribute, when the change is consistent with the rule.