Ontological approach to big data analytics in cybersecurity domain
DOI:
https://doi.org/10.20535/2411-1031.2020.8.2.222559Keywords:
big data analytics, cybersecurity, ontology, thesaurus, unstructured information, metadata, wiki technologies, semantic similarityAbstract
Information security is a dynamic field in which methods and means of protection against threats and their destructive component are rapidly changing and improving, which is a challenge for organizations and society as a whole. Therefore, information systems related to cybersecurity require a constant flow of knowledge from internal and external sources, the volume of which is constantly growing. The introduction of big data sets in the field of cybersecurity provides opportunities for application for the analysis of data containing structured and unstructured data. The application of semantic technologies to search, selection of external big data, and description of knowledge about the cybersecurity domain require new approaches, methods, and algorithms of big data analysis. For selecting relevant data, we are offered a semantic analysis of metadata that accompanies big data and the construction of ontologies that formalize knowledge about metadata, cybersecurity, and the problem that needs to be solved. We are proposed to create a thesaurus of problems based on the domain ontology, which should provide a terminological basis for the integration of ontologies of different levels. The cybersecurity domain has a hierarchical structure, so the presentation of formalized knowledge about it requires the development of the hierarchy of ontologies from top to bottom. For building a thesaurus of problem, it is proposed to use an algorithm that will combine information from information security standards, open natural information resources, dictionaries, and encyclopedias. It is suggested to use semantically marked Wiki-resources, external thesauri, and ontologies to supplement the semantic models of the cybersecurity domain.
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