OSINT Time Series Forecasting Methods Analysis

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dc.contributor.authorFeher, A.
dc.contributor.authorLande, D.
dc.date.accessioned2023-11-22T05:11:34Z
dc.date.available2023-11-22T05:11:34Z
dc.date.issued2023
dc.description.abstractTime series forecasting is an important niche in the modern decision-making and tactics selection process, and in the context of OSINT technology, this approach can help predict events and allow for an effective response to them. For this purpose, LSTM, ARIMA, LPPL (JLS), N-gram were selected as time series forecasting methods, and their simple forms were implemented based on the time series of quantitative mentions of nato, himars, starlink and cyber threats statings obtained and generated using OSINT technology. Based on this, their overall effectiveness and the possibility of using them in combination with OSINT technology to form a forecast of the future were investigated.uk
dc.format.pagerangePp. 39-43uk
dc.identifier.citationFeher, A. OSINT Time Series Forecasting Methods Analysis / A. Feher, D. Lande // Theoretical and Applied Cybersecurity : scientific journal. – 2023. – Vol. 5, Iss. 1. – Pp. 39–43. – Bibliogr. 10 ref.uk
dc.identifier.doihttps://doi.org/10.20535/tacs.2664-29132023.1.287750
dc.identifier.urihttps://ela.kpi.ua/handle/123456789/62357
dc.language.isoenuk
dc.publisherIgor Sikorsky Kyiv Polytechnic Instituteuk
dc.publisher.placeKyivuk
dc.relation.ispartofTheoretical and Applied Cybersecurity: scientific journal, Vol. 5, No. 1uk
dc.subjecttime-seriesuk
dc.subjectpredictionuk
dc.subjectosintuk
dc.subject.udc004.05uk
dc.titleOSINT Time Series Forecasting Methods Analysisuk
dc.typeArticleuk

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Theoretical and Applied Cybersecurity: scientific journal, Vol. 5, No. 1