Overview of Top-Down Role Mining in EmpowerID

The Top-Down Role Mining feature in EmpowerID is an essential tool for administrators looking to automate group memberships within their organizations. This feature streamlines user access management by analyzing organizational roles, locations, and group memberships by leveraging existing data from authoritative systems, such as HR systems. The process focuses on identifying optimal group assignments for users based on their roles and locations, using configurable criteria such as percentage matches and minimum user thresholds. This targeted automation ensures that users are granted appropriate access rights that align with their responsibilities and organizational structure.

Figure 1: Top-Down Role Mining Ascertains the Overlap of People in Role Locations and Groups

A significant advantage of this feature is its capacity to streamline the assignment of users to groups based on their responsibilities and access needs within the organizational hierarchy. Administrators can ensure that users are automatically assigned to the appropriate groups by focusing on specific roles and locations. This targeted approach enhances the accuracy of group assignments and improves overall efficiency in user access management.

Key Benefits

One of the core benefits of Top-Down Role Mining is its ability to perform focused analyses. Administrators can restrict their investigations to specific groups or organizational units, ensuring the analysis remains relevant and manageable. This focus improves the overall performance of the role mining process.

Figure 2: EmpowerID User Interface for Configuring Top-Down Mining

Moreover, the feature allows for customizable criteria, enabling administrators to fine-tune search parameters to view optimal matches. The analysis becomes even more precise by excluding certain groups, such as those with existing RBAC Membership policies roles and EmpowerID dynamic groups.

Understanding the Process

Top-Down Role Mining operates by examining the existing organizational role and location structures maintained by client systems, particularly HR databases. The feature analyzes these structures alongside user assignments to determine which group memberships can be assigned based on the defined criteria.

By implementing this systematic approach, organizations can enhance their security and compliance posture while simplifying the complexities of user access management. This feature's automated nature ensures that as new users are added or as roles change, group memberships are updated accordingly, making it a vital tool for efficient user management.

Process Flow

Top-Down Role Mining involves several key steps:

Data Integration: The process begins by importing existing role and group data from authoritative sources like HR systems.
Role Analysis: The system analyzes the relationships between Business Roles and Locations, assessing which users are associated with specific groups.
Group Assignment: Using a mathematical algorithm, the system identifies levels in the role tree where group memberships can be applied based on user overlap.
Policy Creation: Once optimal matches are found, organizations create Group Membership policies to automate user group assignments in specific roles.

Evaluating Data for Criteria

Once data from external sources has been imported into EmpowerID, evaluating this data is crucial for determining effective matches. This evaluation occurs during the compilation process, which creates records of potential RBAC Group Membership policies based on a subset of group data fed to the compilation engine via a “SetGroup of Groups.” Administrators can also compile all groups for possible matches if desired.

By analyzing the overlap between users in specific organizational roles and their group memberships from the compiled data, organizations can automate group memberships for users in certain roles based on their criteria. Generally speaking, matches that yield higher percentages of overlapping individuals in a given Role and Location, and group are considered better candidates.

Figure 3: Not a Good Candidate to Publish Due to the Low Role Match Overlap

Conversely, if 100% of individuals in a given Role and Location are members of a specific group, that strong correlation indicates a good match for an RBAC Group Membership Policy. Organizations can approve and publish this match, and the system will automatically assign all individuals belonging to the Role and Location to that group going forward. Each time a new person is added to the Role and Location, they will automatically be assigned to the designated group.

Figure 4: Good Candidate to Publish as an RBAC Group Membership Policy

By effectively leveraging the Top-Down Role Mining feature, organizations can automate group memberships through RBAC Group Membership policies, ensuring that users receive the appropriate access to groups based on their roles and locations. This targeted automation streamlines user access management, reduces administrative burdens, and maintains compliance with security standards. EmpowerID's Top-Down Role Mining feature adapts as organizational structures change to ensure access remains aligned with current roles and responsibilities, making it an essential tool for efficient user management.

Next Steps

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