Dynamic User Classification for Authentication Risk Assessment
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Solution Overview
Problem
Conventional authentication systems face challenges in accurately assessing the risk of new users, as they lack behavioral profiles, leading to potential fraudulent requests being misclassified based on static attributes shared with trusted users, thereby ignoring additional risks.
Innovation Solution
Classifying new users into groups based on their current activities using authentication factors, initially placing them in a high-risk group and then reclassifying them based on the specifics of their requests, utilizing distance measures to minimize mismatch with predefined groups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If new users are placed in groups based on static attributes, then authentication can be performed using shared group attributes, but the additional risk associated with new users is ignored
Solution Approach 1:
The patent implements dynamic user classification by transitioning from static attribute-based grouping to activity-based grouping. New users are initially classified into a high-risk group based on their new user status, then dynamically reclassified into appropriate groups based on their actual authentication activities and behavior patterns. This dynamic approach allows the system to adapt user risk assessment over time based on observed behavior rather than relying solely on static attributes.
Solution Approach 2:
The patent applies preliminary action by placing new users into a predefined high-risk group before they have established any authentication history. This preliminary classification allows the system to apply enhanced security measures and monitoring to new users from the outset, while still allowing them to be reclassified into lower-risk groups as they demonstrate trusted behavior patterns over time.
2Reliability
If new users are placed in high-risk groups based on new user status, then additional security measures can be applied, but users with legitimate activities may be incorrectly classified
Solution Approach 1:
The patent implements feedback mechanisms by continuously monitoring new user authentication activities and using this feedback to adjust their group classification. The system compares observed user behavior against expected patterns for different groups and uses this feedback to progressively refine the classification, moving users from initial high-risk categorization to more accurate group assignments as their behavior becomes better understood.
Solution Approach 2:
The system dynamically adjusts user risk classification based on observed authentication patterns. Rather than making a permanent initial classification, the system continuously updates user group assignments based on their actual behavior, allowing for more precise risk assessment that adapts to individual user patterns over time.
3Device complexity
If conventional authentication systems use static group attributes, then implementation is simple, but the system cannot adapt to individual user behaviors
Solution Approach 1:
The patent transforms the authentication system from a static model based on fixed group attributes to a dynamic model that continuously adapts to individual user behaviors. The system monitors authentication activities, learns user patterns, and adjusts classifications accordingly, enabling the system to adapt to individual user behaviors while maintaining manageable complexity through automated learning processes.
Data Source
AI summary
Techniques of authenticating a new user involve classifying a new user as a member of a group based on the new user's current activity. Along these lines, when a new user enrolls in an authentication system, the authentication system places the new user in a group of new users that have not made any requests and are assumed to be high risks of making fraudulent requests. Once the new user makes a request to access a resource, the authentication system classifies the new user as a member of another group according to authentication factors describing activities surrounding the request.