Active Directory Token Bloat Prevention via Group Membership Prediction
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Solution Overview
Problem
In enterprise computer environments managed by Microsoft Active Directory, user authentication tokens often exceed capacity due to excessive group memberships, leading to 'token bloat' and login failures, as they cannot accommodate the increasing information load.
Innovation Solution
A system comprising a predictor, estimator, and preventer that calculates anticipated group membership additions, provides alerts, and modifies or prevents activities that would result in token bloat, using a user authentication token size calculator, group membership estimator, and remediation processes to manage group memberships and access permissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users are granted membership to additional user groups to enhance access permissions, then user access versatility is improved, but the authentication token size increases leading to token bloat and login failures
Solution Approach 1:
The system performs preliminary actions by calculating the current authentication token size and estimating the size after anticipated group membership changes before they occur. This allows the system to predict token bloat conditions in advance and take preventive measures, such as notifying administrators or modifying the anticipated activity, before the token actually exceeds its capacity limit.
Solution Approach 2:
The patent introduces an intermediary prediction mechanism that acts as a mediator between group membership management and authentication token utilization. The system calculates current token size, estimates future token size based on anticipated activities, and provides a buffer prediction that bridges the gap between current state and potential future state, allowing administrators to make informed decisions about group membership changes.
2Adaptability or versatility
If the authentication token size is increased to accommodate more group memberships, then user access permissions are enhanced, but system reliability deteriorates due to login failures
Solution Approach 1:
The system performs preliminary calculations of authentication token size before group membership changes are implemented. By estimating the future token size and comparing it against the maximum capacity, the system can predict potential login failures in advance and prevent them by either blocking the anticipated activity or notifying administrators to adjust the group membership changes.
Solution Approach 2:
The patent applies preliminary anti-action by predicting token bloat conditions before they occur and taking countermeasures to prevent login failures. The system calculates the buffer (remaining capacity) of the authentication token and anticipates whether future group memberships will exceed this buffer, thereby preventing the harmful effect of token bloat and subsequent login failures before they can occur.
3Reliability
If group memberships are monitored and managed more closely to prevent token bloat, then authentication reliability is improved, but system complexity increases
Solution Approach 1:
The system performs self-service by automatically calculating the current authentication token size, estimating future token size based on anticipated group membership changes, and determining whether token bloat will occur. This automated self-assessment reduces the need for manual monitoring and complex management procedures, as the system independently evaluates its own authentication token utilization status and provides predictions to administrators.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors current authentication token size, compares it against maximum capacity, and provides predictive feedback about future token bloat conditions. This feedback loop allows administrators to make informed decisions about group membership management while maintaining relatively simple system architecture, as the complexity is concentrated in automated calculations rather than manual processes.
Data Source
AI summary
A system for preventing an excess user authentication token utilization condition in an enterprise computer environment, the system including an excess user authentication token utilization condition predictor operable for calculating a number of additional group memberships of each of the enterprise users that can be expected to result in an excess user authentication token utilization condition, a group membership estimator operable, for each the enterprise user, for estimating a number of additional group memberships of the enterprise user that will be created by an anticipated activity, and an anticipated excess user authentication token utilization condition alerter operable, before initiation of the anticipated activity, for providing an alert if the anticipated activity can be expected to result in an excess user authentication token utilization condition.