sica-fondt/knowledge/cyber-skills/skills/building-role-mining-for-rbac-optimization/references/workflows.md

Role Mining for RBAC Optimization - Workflows

End-to-End Role Mining Workflow

Phase 1: DATA COLLECTION (Week 1-2)
    ├── Export user-permission data from all identity sources
    │   ├── Active Directory group memberships
    │   ├── Cloud IAM role assignments
    │   ├── Application-level permissions
    │   └── Database access grants
    ├── Collect HR data (job titles, departments, cost centers)
    ├── Normalize data into User-Permission Assignment (UPA) matrix
    └── Clean data: remove disabled accounts, system accounts

Phase 2: ANALYSIS (Week 3-4)
    ├── Run clustering algorithms (hierarchical, k-means)
    ├── Run Formal Concept Analysis for exact role candidates
    ├── Compare results using WSC and coverage metrics
    ├── Identify optimal number of roles via silhouette analysis
    └── Map candidate roles to organizational structure

Phase 3: VALIDATION (Week 5-6)
    ├── Present candidate roles to business unit managers
    ├── Validate each role against job descriptions
    ├── Identify and resolve outlier permissions
    ├── Define role hierarchy (inheritance relationships)
    └── Agree on role names and descriptions

Phase 4: IMPLEMENTATION (Week 7-8)
    ├── Create roles in identity governance platform
    ├── Assign users to validated roles
    ├── Remove individual permission assignments
    ├── Test access for sample users in each role
    └── Document role definitions and approval chain

Phase 5: GOVERNANCE (Ongoing)
    ├── Monitor for permission drift
    ├── Quarterly role effectiveness review
    ├── Re-run mining annually to detect new patterns
    └── Track role count and WSC metrics over time

Data Normalization Workflow

Raw Data Sources
    │
    ├── AD: user → group → permissions
    │       Normalize to: user_id, permission_id
    │
    ├── AWS: user/role → policy → actions
    │       Normalize to: user_id, permission_id
    │
    ├── Azure: user → role → permissions
    │       Normalize to: user_id, permission_id
    │
    └── Applications: user → app_role → features
            Normalize to: user_id, permission_id

Merge all sources → Deduplicate → Create UPA matrix

Role Consolidation Workflow

Mining produces N candidate roles
    │
    ├── Remove roles with < 3 users (outliers)
    │
    ├── Merge roles with > 90% Jaccard similarity
    │
    ├── Identify hierarchical relationships:
    │   └── If Role A permissions ⊂ Role B permissions
    │       → Role A is junior to Role B
    │
    ├── Check for SoD violations:
    │   └── Does any role combine conflicting permissions?
    │       → Split into separate roles if needed
    │
    └── Final role set with hierarchy and constraints