research:www2026 [davidjohnpaul.com]

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====== Bridging the Semantic Gap: A Homonym-Aware Ontology Platform for Cybersecurity Interoperability ======

[[https://doi.org/10.1145/3774905.3795606|Download]]

Hasan, A. B. M. M., Brankovic, L., Sanin, C., and Paul, D. "Bridging the Semantic Gap: A Homonym-Aware Ontology Platform for Cybersecurity Interoperability", WWW Companion '26: Companion Proceedings of the ACM Web Conference 2026, 2026.

===== Abstract =====

The cybersecurity domain exhibits a substantial semantic gap between the operational reality of threat detection and the available static compliance standards (e.g., ISO 27001, NIST SP 800-53). In addition, a disconnect is evident between high-level business goals to protect assets (e.g., Security Services such as Confidentiality) and low-level technical root causes (e.g., Vulnerabilities such as Buffer Overflow). Our previous Systematic Literature Review (SLR) has identified numerous existing ontologies. A persistent structural deficiency is identified: the lack of a dynamic, interoperable platform that supports safe, continuous mapping among Security Services, Security Mechanisms, Attacks, Exploited Vulnerabilities, Attackers, and Assets, with continuous community evaluation. Existing solutions limit practitioners to static, read-only standards for achieving security services, resulting in a lack of agility and a semantic void between the how and the why. This paper proposes a wiki-style, agile, and homonym-aware editing prototype system, which can lead to a novel hybrid cybersecurity ontology with a management and visualisation platform to bridge this semantic gap. We implement the Golden Chain of knowledge identified in prior SLRs (Security Services ↔ Security Mechanisms ↔ Attacks ↔ Vulnerabilities ↔ Attackers ↔ Assets) through three core technical contributions: a) A Concept-Term Separated Architecture that the potential to resolve synonymy and homonymy; b) An Additive Seeder Engine that enables systematic, preserving distributed updates; and c) A Hybrid Contribution Model we bridge CSV → JSON batch processing with granular Web-based expert review. We evaluate this prototype by unifying a number of concepts from different sources (NIST, MITRE, ISO, CyBOK) into a single, cohesive, graph-ready knowledge base. Our results demonstrate that this "living" ontology approach can successfully interpret homonyms (e.g., "Virus" as malware vs. pathogen) and facilitate cross-domain knowledge retrieval.

===== Conference Proceedings =====

[[https://doi.org/10.1145/3774905|WWW Companion '26: Companion Proceedings of the ACM Web Conference 2026]]