AI Identity Graph for Role Validation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Large organizations face challenges in effectively managing and assessing user access entitlements in complex, distributed networked computing environments, leading to inefficiencies and increased security risks due to the complexity of role evolution and lack of tools for monitoring access model health.
Innovation Solution
The implementation of an artificial intelligence-based identity governance system that utilizes network graphs to assess and validate roles, including the creation of role graphs with nodes representing roles and edges representing similarities, allowing for the identification of redundant or similar roles and the consolidation of resources, thereby improving identity governance and reducing computational burdens.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional identity management methods are used in large organizations, then access control policies can be implemented, but the complexity of managing user access entitlements across thousands of users and hundreds of applications increases significantly
Solution Approach 1:
The patent introduces an identity graph as an intermediary data structure that models relationships between users, roles, applications, and entitlements. This graph serves as a mediator that simplifies the complex web of access relationships by providing a unified representation, enabling automated analysis and validation of access policies without manually managing each individual entitlement assignment across thousands of users and hundreds of applications.
2Reliability
If comprehensive compliance monitoring is applied to all users and applications, then security coverage is maximized, but time and resources are wasted on low-risk areas
Solution Approach 1:
The patent applies local quality by enabling differentiated compliance monitoring based on risk characteristics of different users, roles, and applications. The system identifies and focuses intensive monitoring resources on high-risk areas where access anomalies are more likely to occur, while reducing monitoring intensity for low-risk areas. This selective approach maintains comprehensive security coverage while optimizing resource allocation across the enterprise environment.
3Adaptability or versatility
If role structures evolve to meet changing business needs, then adaptability improves, but the difficulty of detecting and measuring role similarities and redundancies increases
Solution Approach 1:
The patent replaces manual role analysis and comparison mechanisms with automated computational methods. The system uses the identity graph to automatically detect role similarities, redundancies, and evolution patterns through algorithmic analysis of entitlement relationships. This substitution of mechanical manual processes with automated computing enables continuous monitoring of role structures as they evolve, making it feasible to detect and measure role similarities even in dynamic environments with frequent changes.
4Ease of manufacture
If no baseline measurement of identity compliance is established, then implementation is simpler, but the ability to quantify improvements and demonstrate effective controls is lost
Solution Approach 1:
The patent implements preliminary action by establishing baseline compliance measurements and role relationship mappings early in the identity management process. The system creates an initial state representation of the identity graph that serves as a reference point for future comparisons. This baseline enables organizations to quantify improvements in compliance and security effectiveness over time, providing measurable evidence of control effectiveness while the automated nature of baseline establishment minimizes the additional implementation complexity.
Data Source
AI summary
Systems and methods for embodiments of a graph based artificial intelligence systems for identity management are disclosed. Embodiments of the identity management systems disclosed herein may utilize a network graph approach to analyzing roles of a distributed networked enterprise computing environment. Specifically, in certain embodiments, an artificial intelligence based identity management systems may utilize role graphs to assess the role structure of a distributed enterprise computing environment.