Taxonomies using the clique percolation method for building a threats observatory

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dc.contributor.authorTorres, Romina
dc.contributor.authorGonzález, Nicolás
dc.contributor.authorCabrera, Mathías
dc.contributor.authorSalas, Rodrigo
dc.date.accessioned2022-11-30T02:47:03Z
dc.date.available2022-11-30T02:47:03Z
dc.date.issued2021
dc.description.abstractCyberattacks are increasing every day, demanding that security incident response teams proactively determine potential threats early. Although social networks such as Twitter are a rich and up-to-date source of information where users use to tweet about different topics, it is complex to efficiently and effectively obtain results that support decision-making on a specific subject, such as cyberattacks. Therefore, in this work, we propose to use an offline mining process based on the clique percolation method over a corpus of tweets in order to generate an indexed knowledge base about cyberattacks. Results are promising to observe threats under evolution. Then, to show results properly, we generate an observatory prototype to allow cybersecurity researchers to explore threats over time and space.en_ES
dc.facultadFacultad de Ingenieríaen_ES
dc.file.nameTorres_Tax2021.pdf
dc.identifier.citationR. Torres, N. González, M. Cabrera and R. Salas, "Taxonomies using the clique percolation method for building a threats observatory," 2021 XLVII Latin American Computing Conference (CLEI), 2021, pp. 1-5, doi: 10.1109/CLEI53233.2021.9639945.en_ES
dc.identifier.doi10.1109/CLEI53233.2021.9639945.
dc.identifier.urihttp://repositoriobibliotecas.uv.cl/handle/uvscl/7561
dc.languageen
dc.publisherIEEE
dc.source2021 XLVII Latin American Computing Conference (CLEI)
dc.titleTaxonomies using the clique percolation method for building a threats observatory
dc.typeArticulo
uv.departamentoEscuela de Ingenieria Informatica
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