dc.contributor.author | Takko, Tuomas | |
dc.contributor.author | Bhattacharya, Kunal | |
dc.contributor.author | Lehto, Martti | |
dc.contributor.author | Jalasvirta, Pertti | |
dc.contributor.author | Cederberg, Aapo | |
dc.contributor.author | Kaski, Kimmo | |
dc.date.accessioned | 2023-02-06T09:24:37Z | |
dc.date.available | 2023-02-06T09:24:37Z | |
dc.date.issued | 2023 | |
dc.identifier.citation | Takko, T., Bhattacharya, K., Lehto, M., Jalasvirta, P., Cederberg, A., & Kaski, K. (2023). Knowledge mining of unstructured information : application to cyber domain. <i>Scientific Reports</i>, <i>13</i>, Article 1714. <a href="https://doi.org/10.1038/s41598-023-28796-6" target="_blank">https://doi.org/10.1038/s41598-023-28796-6</a> | |
dc.identifier.other | CONVID_176734449 | |
dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/85359 | |
dc.description.abstract | Information on cyber-related crimes, incidents, and conflicts is abundantly available in numerous open online sources. However, processing large volumes and streams of data is a challenging task for the analysts and experts, and entails the need for newer methods and techniques. In this article we present and implement a novel knowledge graph and knowledge mining framework for extracting the relevant information from free-form text about incidents in the cyber domain. The computational framework includes a machine learning-based pipeline for generating graphs of organizations, countries, industries, products and attackers with a non-technical cyber-ontology. The extracted knowledge graph is utilized to estimate the incidence of cyberattacks within a given graph configuration. We use publicly available collections of real cyber-incident reports to test the efficacy of our methods. The knowledge extraction is found to be sufficiently accurate, and the graph-based threat estimation demonstrates a level of correlation with the actual records of attacks. In practical use, an analyst utilizing the presented framework can infer additional information from the current cyber-landscape in terms of the risk to various entities and its propagation between industries and countries. | en |
dc.format.mimetype | application/pdf | |
dc.language.iso | eng | |
dc.publisher | Nature Publishing Group | |
dc.relation.ispartofseries | Scientific Reports | |
dc.rights | CC BY 4.0 | |
dc.subject.other | computational science | |
dc.subject.other | computer science | |
dc.subject.other | information technology | |
dc.title | Knowledge mining of unstructured information : application to cyber domain | |
dc.type | article | |
dc.identifier.urn | URN:NBN:fi:jyu-202302061640 | |
dc.contributor.laitos | Informaatioteknologian tiedekunta | fi |
dc.contributor.laitos | Faculty of Information Technology | en |
dc.contributor.oppiaine | Tietojärjestelmätiede | fi |
dc.contributor.oppiaine | Information Systems Science | en |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | |
dc.type.coar | http://purl.org/coar/resource_type/c_2df8fbb1 | |
dc.description.reviewstatus | peerReviewed | |
dc.relation.issn | 2045-2322 | |
dc.relation.volume | 13 | |
dc.type.version | publishedVersion | |
dc.rights.copyright | © The Author(s) 2023 | |
dc.rights.accesslevel | openAccess | fi |
dc.subject.yso | tietojenkäsittelytieteet | |
dc.subject.yso | laskennallinen tiede | |
dc.subject.yso | tietotekniikka | |
dc.format.content | fulltext | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p21029 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p21978 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p5462 | |
dc.rights.url | https://creativecommons.org/licenses/by/4.0/ | |
dc.relation.doi | 10.1038/s41598-023-28796-6 | |
jyx.fundinginformation | TT, KB, ML and KK acknowledge research project funding from Cyberwatch Finland. TT acknowledges funding from the Vilho, Yrjö and Kalle Väisälä Foundation of the Finnish Academy of Science and Letters. | |
dc.type.okm | A1 | |