Cybersecurity in AI-Driven Casual Network Formation

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dc.contributor.authorLande, Dmytro
dc.contributor.authorFeher, Anatolii
dc.contributor.authorStrashnoy, Leonard
dc.date.accessioned2023-11-23T08:31:32Z
dc.date.available2023-11-23T08:31:32Z
dc.date.issued2023
dc.description.abstractThe paper describes a methodology for forming thematic causal networks using artificial intelligence and automating the processes of their visualization. The presented methodology is considered on the example of ChatGPT, as an artificial intelligence for analyzing the space of texts and building concepts of causal relationships, and their further visualization is demonstrated on the example of Gephi and CSV2Graph programs. The effectiveness of the disaggregated method in relation to traditional methods for solving such problems is shown by integrating the means of intelligent text analytics and graphical network analysis on the example of the problem of data leakage in information systems and a selection of news clippings on the selected cybersecurity topic.uk
dc.format.pagerangePp. 105-113uk
dc.identifier.citationLande, D. Cybersecurity in AI-Driven Casual Network Formation / Dmytro Lande, Anatolii Feher, Leonard Strashnoy // Theoretical and Applied Cybersecurity : scientific journal. – 2023. – Vol. 5, Iss. 2. – Pp. 105–113. – Bibliogr. 6 ref.uk
dc.identifier.doihttps://doi.org/10.20535/tacs.2664-29132023.2.287139
dc.identifier.urihttps://ela.kpi.ua/handle/123456789/62416
dc.language.isoenuk
dc.publisherIgor Sikorsky Kyiv Polytechnic Instituteuk
dc.publisher.placeKyivuk
dc.relation.ispartofTheoretical and Applied Cybersecurity: scientific journal, Vol. 5, No. 2uk
dc.subjectChatGPTuk
dc.subjectCausal networksuk
dc.subjectArtificial intelligenceuk
dc.subjectSubject matter modelsuk
dc.subjectGraph visualizationuk
dc.subjectData leakageuk
dc.subjectCybersecurityuk
dc.subject.udc004.05uk
dc.titleCybersecurity in AI-Driven Casual Network Formationuk
dc.typeArticleuk

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Theoretical and Applied Cybersecurity: scientific journal, Vol. 5, No. 2