Comparison analysis between strict ontologies and fuzzy ontologies
DOI:
https://doi.org/10.20535/tacs.2664-29132024.2.317249Abstract
Ontological modeling has been important in the field of cybersecurity, but with the growing use of artificial intelligence in various processes related to cybersecurity, it has become an increasingly relevant area for research every new year. Ontologies can serve as a primary source of knowledge for artificial intelligence models and as a "sequence of actions" in different processes. Typically, strict ontologies were used due to their formalized structure, but they did not fully capture processes that involve fuzzy contexts of actions or results. The aim of this article is to present and analyze different ontologies, both strict and fuzzy, that are used or could be used in the field of cybersecurity and related processes, demonstrating their similarities, differences, and areas of application.
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