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Measuring Zero-Trust Maturity in Industrial Multi-Cloud

Industrial multi-cloud ecosystems require continuous verification models to secure heterogeneous cyber-physical environments against sophisticated persistent threats. This framework establishes multi-dimensional maturity assessment criteria grounded in NIST 800-207 guidelines, continuous identity posture validation, and real-time telemetry orchestration. The resulting evaluation structure bridges enterprise policy governance and operational technology latency constraints to guide secure cloud-edge convergence.

Arbetets mål

Evaluate maturity dimensions of Zero-Trust Architecture across industrial multi-cloud environments to establish a standardized assessment framework.

Metodik

Comparative secondary synthesis of cybersecurity standards, maturity models, and peer-reviewed multi-cloud architectural frameworks.

Vetenskaplig nyhet

Bridges enterprise zero-trust maturity assessment with real-time operational technology latency constraints across heterogeneous cloud providers.

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Master's Thesis (2 year)

Degree:
Measuring Zero-Trust Maturity in Industrial Multi-Cloud

Author:

Group

First M. Last

Advisor:

Dr. First Last

City, 2026

Contents

Sammanfattning and Abstract
Introduction
Problem Formulation and Research Objectives
Theoretical Foundations of Industrial Zero-Trust Architectures
Multi-Cloud Governance and Dynamic Policy Enforcement Engines
Cyber-Physical Telemetry and Edge-Fog Microsegmentation
Maturity Modeling Methodologies for Distributed Environments
Evaluation Criteria and Verification Artifacts Across Cloud Platforms
Operational Technology Constraints and Latency Trade-Offs
Discussion: Integration Barriers and Governance Realities
Critical Gaps in Autonomous Anomaly Detection and Access Orchestration
AI-deklaration
Conclusions and Strategic Recommendations
Referenser

Introduction

Industrial operational environments increasingly rely on distributed multi-cloud ecosystems and Industrial Internet of Things integrations to maintain scalable operational capabilities and real-time processing efficiency. However, traditional perimeter-based security perimeters fail against advanced insider risks and complex lateral movement across heterogeneous platforms [1], [6]. Zero-Trust Architecture establishes continuous verification, dynamic policy enforcement, and granular microsegmentation across all network assets regardless of physical location [1], [3]. Assessing the progression and effectiveness of these deployments requires structured maturity frameworks tailored to industrial constraints.

Despite widespread adoption of zero-trust principles across enterprise software systems, applying these constructs to industrial multi-cloud settings introduces distinct architectural tensions. Operational technology infrastructure imposes strict real-time availability and ultra-low latency demands that often conflict with continuous multi-factor authentication cycles and dynamic trust scoring [2], [6]. Furthermore, disparate cloud service providers utilize distinct identity stores and telemetry standards, complicating uniform policy orchestration and holistic maturity evaluation [3], [7]. Without standardized metric systems, organizations struggle to measure genuine zero-trust implementation depth across legacy and cloud-native layers [5].

This study synthesizes contemporary maturity assessment literature, architectural standards such as NIST 800-207, and cross-cloud policy governance models to establish a comprehensive maturity evaluation framework for industrial multi-cloud systems [1], [2], [5]. By categorizing identity governance, behavioral telemetry, microsegmentation, and automated incident response, this framework provides theoretical clarity and practical assessment benchmarks. The resulting analysis establishes systematic criteria for diagnosing capability gaps, mitigating operational latency risks, and achieving resilient multi-cloud cyber-physical security postures [6], [7].

Critical Gaps in Autonomous Anomaly Detection and Access Orchestration

Evaluating zero-trust maturity within industrial multi-cloud environments reveals critical tensions between centralized policy governance and localized operational requirements. Standard enterprise frameworks prioritize continuous multi-factor authentication, cryptographic posture verification, and centralized policy decision points [1], [7]. However, when extended across multi-cloud topologies that interface with operational technology and industrial control networks, these mechanisms encounter strict latency thresholds [6]. Centralized policy engines located across remote cloud environments can introduce verification delays that conflict with real-time industrial communication standards [3], [6]. Furthermore, disparate cloud service providers employ divergent access management primitives, which impedes cohesive policy orchestration and creates fragmented trust scoring [3], [7]. A critical limitation identified in the literature is that existing maturity models frequently treat cloud-native infrastructure as an isolated domain, underestimating the friction generated by legacy protocol translation and edge device computational limits [1], [6]. Consequently, higher maturity scores in identity management do not inherently translate into resilient microsegmentation across distributed hybrid tiers unless continuous anomaly detection and context-aware enforcement are harmonized across all participating cloud fabrics [3], [7].

References

  1. Zero Trust Architecture and Enterprise Applications
    Özkan Canay, Halil Arslan
    DOI-länk
  2. AI-Driven Anomaly Detection and Zero Trust Frameworks
    Elyson De La Cruz, Chandra Prakash, Shaila Rana
    DOI-länk
  3. Cybersecurity Challenges in Multi-Cloud Networking: A Zero-Trust Security Framework for Secure Data Access
    Jaya Chandra Myla
    DOI-länk
  4. Cybersecurity Framework for Multi-Cloud Deployment Pipelines: A Zero-Trust Architecture for Inter-Platform Data Protection
    Uttama Reddy Sanepalli
  5. Zero trust cybersecurity: Critical success factors and A maturity assessment framework
    William Yeoh, Marina Liu, Malcolm Shore et al.
  6. Zero-Trust Architecture for Energy Grid Cybersecurity: Multi-Layered Authentication and Continuous Verification Framework
    Kazeem Mohammed
  7. Zero-Trust Cloud Access Management (ZTCAM) Framework for Multi-Cloud Enterprise Environments
    Pankaj Gupta
  8. Federated Learning and Zero Trust Framework for Anomaly Detection in Distributed IIoT-Cloud Systems
    Fadi Bata, Mahmoud Aljawarneh, Qais Al-Na'amneh et al.

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Measuring Zero-Trust Maturity in Industrial Multi-Cloud | Forskning | Aicademy