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All Journal RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JUKI : Jurnal Komputer dan Informatika J-Icon : Jurnal Komputer dan Informatika Global Science: Journal of Information Technology and Computer Science
Meiton Boru
Universitas Nusa Cendana
Computer Science & IT Engineering

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From Cryptography To Risk: Network Topology Of Cybersecurity Knowledge Simon Simarmata; Meiton Boru
Global Science: Journal of Information Technology and Computer Science Vol. 2 No. 1 (2026): March: Global Science: Journal of Information Technology and Computer Science
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | 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
Co-Authors Adriana Fanggidae Arfan Y Mauko Arfan Y Mauko Aristop Solle Beny R E Manu Clarissa Elfira Amos Pah D D Anggiawan Emerensye S. Y. Pandie Farmi S Radjatadoe Frensile Susanti Ndoen Hepiyana V Runesi Kornelis L Maria Louise Ludgardis Muku Maria P C Seran Nelci D Rumlaklak Novi Penna Rowin Djuli Sebastianus A S Mola Sebastianus A. S. Mola Sebastianus Adi Santoso Mola Sihotang, Dony Martinus Simon Simarmata Tiwuk Widiastuti Yelly Y Nabuasa