Security evaluation framework for cloud ERP systems using NIST and ISO standards
Abstract
Enterprise Resource Planning (ERP) systems serve as critical infrastructure for modern organizations, yet their security assessment lacks standardized evaluation frameworks. This study develops and applies a structured Security Maturity Assessment Framework (SMAF) grounded in NIST Cybersecurity Framework (CSF) 2.0 and ISO/IEC 27001:2022 standards to evaluate eleven cloud-based and hybrid ERP platforms, including both full-suite ERP systems and widely adopted inventory and manufacturing management systems that serve as ERP alternatives for SMEs. Using a weighted multi-criteria decision analysis (MCDA) approach validated by expert surveys ([Formula: see text]) and vendor documentation analysis, we assess security across five domains: authentication mechanisms, encryption protocols, access control models, vulnerability management, and compliance certifications. Our framework introduces quantifiable security maturity scores ranging from 1 (basic) to 5 (advanced), enabling objective comparison across platforms. Results indicate that enterprise-grade solutions (Oracle NetSuite OneWorld, SAP Business One Professional, Microsoft Dynamics 365) achieve consistently higher security maturity scores ([Formula: see text], [Formula: see text]) compared to SME-targeted solutions ([Formula: see text], [Formula: see text]), though small per-segment sample sizes ([Formula: see text]-4) limit formal statistical inference. We extend our analysis to emerging security paradigms including Zero-Trust Architecture (ZTA) integration, federated learning for privacy-preserving analytics, blockchain-based audit trails, and digital twin implementations for Industry 5.0 alignment. The proposed SMAF provides organizations with an evidence-based methodology for ERP security evaluation, addressing a critical gap in both academic literature and practitioner guidance.
Fields of Study & Subjects
ERP Systems Implementation and Impact
Information and Cyber Security
Cloud Data Security Solutions
Publication details
- Journal / source
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Volume
- 16
- Issue
- 1
- Publication date
- 3 April 2026
- Language
- EN