The PRCIM
Framework.
Proactive Risk-Centric Identity Management: A novel approach to securing high-value financial transactions in zero-trust environments.
Traditional Role-Based Access Control (RBAC) models are static and fail to account for the dynamic nature of modern threats. This paper introduces the PRCIM framework, which integrates AI-driven anomaly detection with Zero Trust principles to create a 'Self-Healing' validation layer. By analyzing user behavior session-by-session, PRCIM eliminates 'Authorized User' fraud before it occurs.
1. Introduction
In the era of cloud computing, the perimeter is porous. Legacy security models that rely on static credentials are no match for sophisticated phishing and credential stuffing attacks. Once an attacker bypasses the initial authentication, they often have lateral movement capabilities restricted only by static permissions.
2. The Problem with RBAC
Role-Based Access Control (RBAC) assumes that if a user has the 'Admin' role, every action they take is legitimate. It lacks context. PRCIM challenges this by adding a layer of Dynamic Risk Scoring.
3. The PRCIM Solution
PRCIM operates on three core pillars:
- Continuous Monitoring: analyzing session tokens and behavioral biometrics.
- Risk Quantification: assigning a real-time risk score (0-100) to every transaction.
- Automated Remediation: triggering step-up authentication or session revocation instantly if the score exceeds a threshold.
4. Conclusion
The PRCIM framework demonstrates that security does not have to be a bottleneck. By making access conditional on risk rather than just role, we achieve a higher security posture with less friction for legitimate users.