From Cryptography To Risk: Network Topology Of Cybersecurity Knowledge

Simarmata ; Simon ; Boru ; Meiton
Journal of Information Technology and Computer Sci... 📅 2026 Vol 2, No 1 🔗 DOI: 10.70062/globalscience.v2i1.189
Abstract
Inconsistent terminology across cybersecurity frameworks undermines global governance and interoperability. The National Institute of Standards and Technology Cybersecurity Framework (NIST CSF 2.0) and ISO/IEC 27001:2022 share similar objectives but diverge semantically in defining risk, control, and resilience. This semantic gap causes difficulties in compliance mapping and automated policy translation. Research Objectives: This study aims to analyze the semantic similarity and divergence between NIST and ISO/IEC 27000 terminologies, identify conceptual structures influencing interoperability, and propose an AI-assisted foundation for harmonizing cybersecurity language globally. Methodology: A mixed-method semantic comparative design integrates Natural Language Processing (NLP) and ontology mapping. Using the nist_glossary.csv dataset and ISO vocabularies, terms were normalized and analyzed via cosine similarity using sentence-transformer embeddings. Ontological alignment was visualized through the Semantic Threat Graph (STG) and validated by certified experts using Cohen’s Kappa reliability tests. Results: From 672 term pairs, results show 40.9% high semantic equivalence, 38.8% partial overlap, and 20.3% semantic divergence. Strongest alignment appears in “Protect” and “Identify” domains, while divergences occur in governance and recovery-related terms. Ontology mapping revealed three conceptual clusters—Risk Governance, Technical Safeguards, and Organizational Readiness. Conclusions: Findings confirm a 79.7% total semantic alignment, indicating strong potential for harmonizing global cybersecurity standards. The study contributes an empirical model combining computational linguistics and AI-based ontology mapping to establish semantic interoperability, enabling unified cybersecurity governance and AI-driven compliance automation.
Keywords: Semantic Interoperability; Ontology Mapping; Cybersecurity Frameworks; Terminology Alignment; AI Harmonization
Keywords
Semantic Search; Cybersecurity Ontologies; Transformer Models; Terminology Alignment; Semantic Interoperability
How to Cite

Simarmata, et al. (2026). From Cryptography To Risk: Network Topology Of Cybersecurity Knowledge. Journal of Information Technology and Computer Science, 2(1). https://doi.org/10.70062/globalscience.v2i1.189

Simarmata, Simon; Boru, Meiton, "From Cryptography To Risk: Network Topology Of Cybersecurity Knowledge," Journal of Information Technology and Computer Science, vol. 2, no. 1, 2026.

Simarmata, Simon; Boru, Meiton. "From Cryptography To Risk: Network Topology Of Cybersecurity Knowledge." Journal of Information Technology and Computer Science, vol. 2, no. 1, 2026.

Simarmata, Simon; Boru, Meiton. "From Cryptography To Risk: Network Topology Of Cybersecurity Knowledge." Journal of Information Technology and Computer Science 2, no. 1 (2026).

Simarmata, et al. (2026) 'From Cryptography To Risk: Network Topology Of Cybersecurity Knowledge', Journal of Information Technology and Computer Science, 2(1). doi: 10.70062/globalscience.v2i1.189.

Simarmata, Simon; Boru, Meiton. From Cryptography To Risk: Network Topology Of Cybersecurity Knowledge. Journal of Information Technology and Computer Science. 2026;2(1).

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